convert : allow partial update to the chkhsh pre-tokenizer list (#13847)

* convert : allow partial update to the chkhsh pre-tokenizer list

* code style

* update tokenizer out

* rm inp/out files for models not having gguf

* fixed hash for glm

* skip nomic-bert-moe test

* Update convert_hf_to_gguf_update.py

* fix minerva-7b hash

* rm redundant import
This commit is contained in:
Xuan-Son Nguyen
2025-05-30 12:24:37 +02:00
committed by GitHub
parent 291f2b6913
commit 07e4351ce6
43 changed files with 159 additions and 1208 deletions

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@ -674,12 +674,12 @@ class TextModel(ModelBase):
if chkhsh == "8aeee3860c56296a157a1fe2fad249ec40aa59b1bb5709f4ade11c4e6fe652ed": if chkhsh == "8aeee3860c56296a157a1fe2fad249ec40aa59b1bb5709f4ade11c4e6fe652ed":
# ref: https://huggingface.co/tiiuae/falcon-7b # ref: https://huggingface.co/tiiuae/falcon-7b
res = "falcon" res = "falcon"
if chkhsh == "9d032fcbd5501f4a38150912590928bfb36091efb5df11b8e2124b0390e3fb1e":
# ref: https://huggingface.co/tiiuae/Falcon3-7B-Base
res = "falcon3"
if chkhsh == "0876d13b50744004aa9aeae05e7b0647eac9d801b5ba4668afc01e709c15e19f": if chkhsh == "0876d13b50744004aa9aeae05e7b0647eac9d801b5ba4668afc01e709c15e19f":
# ref: https://huggingface.co/BAAI/bge-small-en-v1.5 # ref: https://huggingface.co/BAAI/bge-small-en-v1.5
res = "bert-bge" res = "bert-bge"
if chkhsh == "9d032fcbd5501f4a38150912590928bfb36091efb5df11b8e2124b0390e3fb1e":
# ref: https://huggingface.co/tiiuae/Falcon3-7B-Base
res = "falcon3"
if chkhsh == "8e62295832751ca1e8f92f2226f403dea30dc5165e448b5bfa05af5340c64ec7": if chkhsh == "8e62295832751ca1e8f92f2226f403dea30dc5165e448b5bfa05af5340c64ec7":
# ref: https://huggingface.co/BAAI/bge-large-zh-v1.5 # ref: https://huggingface.co/BAAI/bge-large-zh-v1.5
res = "bert-bge-large" res = "bert-bge-large"
@ -731,9 +731,6 @@ class TextModel(ModelBase):
if chkhsh == "7967bfa498ade6b757b064f31e964dddbb80f8f9a4d68d4ba7998fcf281c531a": if chkhsh == "7967bfa498ade6b757b064f31e964dddbb80f8f9a4d68d4ba7998fcf281c531a":
# ref: https://huggingface.co/jinaai/jina-embeddings-v2-base-code # ref: https://huggingface.co/jinaai/jina-embeddings-v2-base-code
res = "jina-v2-code" res = "jina-v2-code"
if chkhsh == "b6e8e1518dc4305be2fe39c313ed643381c4da5db34a98f6a04c093f8afbe99b" or chkhsh == "81d72c7348a9f0ebe86f23298d37debe0a5e71149e29bd283904c02262b27516":
# ref: https://huggingface.co/THUDM/glm-4-9b-chat
res = "chatglm-bpe"
if chkhsh == "7fc505bd3104ca1083b150b17d088b59534ede9bde81f0dd2090967d7fe52cee": if chkhsh == "7fc505bd3104ca1083b150b17d088b59534ede9bde81f0dd2090967d7fe52cee":
# ref: https://huggingface.co/LumiOpen/Viking-7B # ref: https://huggingface.co/LumiOpen/Viking-7B
res = "viking" res = "viking"
@ -764,9 +761,6 @@ class TextModel(ModelBase):
if chkhsh == "60824e3c0d9401f89943cbb2fff727f0e2d4c545ba4df2d6e4f09a6db0f5b450": if chkhsh == "60824e3c0d9401f89943cbb2fff727f0e2d4c545ba4df2d6e4f09a6db0f5b450":
# ref: https://huggingface.co/facebook/chameleon-7b # ref: https://huggingface.co/facebook/chameleon-7b
res = "chameleon" res = "chameleon"
if chkhsh == "1431a23e583c97432bc230bff598d103ddb5a1f89960c8f1d1051aaa944d0b35":
# ref: https://huggingface.co/sapienzanlp/Minerva-7B-base-v1.0
res = "minerva-7b"
if chkhsh == "8b5a93ed704057481f240da0be7e7dca721d7f8f4755263b6807227a2cbeae65": if chkhsh == "8b5a93ed704057481f240da0be7e7dca721d7f8f4755263b6807227a2cbeae65":
# ref: https://huggingface.co/sentence-transformers/stsb-roberta-base # ref: https://huggingface.co/sentence-transformers/stsb-roberta-base
res = "roberta-bpe" res = "roberta-bpe"
@ -797,15 +791,24 @@ class TextModel(ModelBase):
if chkhsh == "d353350c764d8c3b39c763113960e4fb4919bea5fbf208a0e3b22e8469dc7406": if chkhsh == "d353350c764d8c3b39c763113960e4fb4919bea5fbf208a0e3b22e8469dc7406":
# ref: https://huggingface.co/meta-llama/Llama-4-Scout-17B-16E-Instruct # ref: https://huggingface.co/meta-llama/Llama-4-Scout-17B-16E-Instruct
res = "llama4" res = "llama4"
if chkhsh == "a1336059768a55c99a734006ffb02203cd450fed003e9a71886c88acf24fdbc2":
# ref: https://huggingface.co/THUDM/glm-4-9b-hf
res = "glm4"
if chkhsh == "0e9433cbbb161f89e264eb32e8e64bfe69e834973ffca5d41d3948a604a3e2a3": if chkhsh == "0e9433cbbb161f89e264eb32e8e64bfe69e834973ffca5d41d3948a604a3e2a3":
# ref: https://huggingface.co/mistral-community/pixtral-12b # ref: https://huggingface.co/mistral-community/pixtral-12b
res = "pixtral" res = "pixtral"
if chkhsh == "d5f1dd6f980fec569fb218a81a7658ac45fc56b38c5a0adeb1c232fbe04ef5ec": if chkhsh == "d5f1dd6f980fec569fb218a81a7658ac45fc56b38c5a0adeb1c232fbe04ef5ec":
# ref: https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Base # ref: https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Base
res = "seed-coder" res = "seed-coder"
if chkhsh == "b6e8e1518dc4305be2fe39c313ed643381c4da5db34a98f6a04c093f8afbe99b":
# ref: https://huggingface.co/THUDM/glm-4-9b-chat
res = "chatglm-bpe"
if chkhsh == "81d72c7348a9f0ebe86f23298d37debe0a5e71149e29bd283904c02262b27516":
# ref: https://huggingface.co/THUDM/glm-4-9b-chat
res = "chatglm-bpe"
if chkhsh == "a1336059768a55c99a734006ffb02203cd450fed003e9a71886c88acf24fdbc2":
# ref: https://huggingface.co/THUDM/glm-4-9b-hf
res = "glm4"
if chkhsh == "1431a23e583c97432bc230bff598d103ddb5a1f89960c8f1d1051aaa944d0b35":
# ref: https://huggingface.co/sapienzanlp/Minerva-7B-base-v1.0
res = "minerva-7b"
if res is None: if res is None:
logger.warning("\n") logger.warning("\n")

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@ -1,28 +1,6 @@
#!/usr/bin/env python3 #!/usr/bin/env python3
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
# This script downloads the tokenizer models of the specified models from Huggingface and
# generates the get_vocab_base_pre() function for convert_hf_to_gguf.py
#
# This is necessary in order to analyze the type of pre-tokenizer used by the model and
# provide the necessary information to llama.cpp via the GGUF header in order to implement
# the same pre-tokenizer.
#
# ref: https://github.com/ggml-org/llama.cpp/pull/6920
#
# Instructions:
#
# - Add a new model to the "models" list
# - Run the script with your huggingface token:
#
# python3 convert_hf_to_gguf_update.py <huggingface_token>
#
# - The convert_hf_to_gguf.py script will have had its get_vocab_base_pre() function updated
# - Update llama.cpp with the new pre-tokenizer if necessary
#
# TODO: generate tokenizer tests for llama.cpp
#
import logging import logging
import os import os
import pathlib import pathlib
@ -32,6 +10,7 @@ import requests
import sys import sys
import json import json
import shutil import shutil
import argparse
from hashlib import sha256 from hashlib import sha256
from enum import IntEnum, auto from enum import IntEnum, auto
@ -41,6 +20,11 @@ logging.basicConfig(level=logging.DEBUG)
logger = logging.getLogger("convert_hf_to_gguf_update") logger = logging.getLogger("convert_hf_to_gguf_update")
sess = requests.Session() sess = requests.Session()
convert_py_pth = pathlib.Path("convert_hf_to_gguf.py")
convert_py = convert_py_pth.read_text(encoding="utf-8")
hf_token_pth = pathlib.Path.home() / ".cache" / "huggingface" / "token"
hf_token = hf_token_pth.read_text(encoding="utf-8").strip() if hf_token_pth.exists() else None
class TOKENIZER_TYPE(IntEnum): class TOKENIZER_TYPE(IntEnum):
SPM = auto() SPM = auto()
@ -49,20 +33,49 @@ class TOKENIZER_TYPE(IntEnum):
UGM = auto() UGM = auto()
DOC_STRING = """
This script downloads the tokenizer models of the specified models from Huggingface and
generates the get_vocab_base_pre() function for convert_hf_to_gguf.py
/!\\ It is intended to be used by contributors and is not meant to be run by end users
This is necessary in order to analyze the type of pre-tokenizer used by the model and
provide the necessary information to llama.cpp via the GGUF header in order to implement
the same pre-tokenizer.
ref: https://github.com/ggml-org/llama.cpp/pull/6920
Instructions:
- Add a new model to the "models" list
- Run the script with your huggingface token
By default, token will be read from ~/.cache/huggingface/token
- The convert_hf_to_gguf.py script will have had its get_vocab_base_pre() function updated
- Update llama.cpp with the new pre-tokenizer if necessary
"""
# TODO: generate tokenizer tests for llama.cpp
parser = argparse.ArgumentParser(description=DOC_STRING, formatter_class=argparse.RawTextHelpFormatter)
parser.add_argument(
"--full", action="store_true",
help="download full list of models - make sure you have access to all of them",
)
parser.add_argument(
"hf_token",
help="optional HF token",
nargs="?",
)
args = parser.parse_args()
hf_token = args.hf_token if args.hf_token is not None else hf_token
if hf_token is None:
logger.error("HF token is required. Please provide it as an argument or set it in ~/.cache/huggingface/token")
sys.exit(1)
# TODO: this string has to exercise as much pre-tokenizer functionality as possible # TODO: this string has to exercise as much pre-tokenizer functionality as possible
# will be updated with time - contributions welcome # will be updated with time - contributions welcome
CHK_TXT = '\n \n\n \n\n\n \t \t\t \t\n \n \n \n \n🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天 ------======= нещо на Български \'\'\'\'\'\'```````\"\"\"\"......!!!!!!?????? I\'ve been \'told he\'s there, \'RE you sure? \'M not sure I\'ll make it, \'D you like some tea? We\'Ve a\'lL' CHK_TXT = '\n \n\n \n\n\n \t \t\t \t\n \n \n \n \n🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天 ------======= нещо на Български \'\'\'\'\'\'```````\"\"\"\"......!!!!!!?????? I\'ve been \'told he\'s there, \'RE you sure? \'M not sure I\'ll make it, \'D you like some tea? We\'Ve a\'lL'
if len(sys.argv) == 2:
token = sys.argv[1]
if not token.startswith("hf_"):
logger.info("Huggingface token seems invalid")
logger.info("Usage: python convert_hf_to_gguf_update.py <huggingface_token>")
sys.exit(1)
else:
logger.info("Usage: python convert_hf_to_gguf_update.py <huggingface_token>")
sys.exit(1)
# TODO: add models here, base models preferred # TODO: add models here, base models preferred
models = [ models = [
{"name": "llama-spm", "tokt": TOKENIZER_TYPE.SPM, "repo": "https://huggingface.co/meta-llama/Llama-2-7b-hf", }, {"name": "llama-spm", "tokt": TOKENIZER_TYPE.SPM, "repo": "https://huggingface.co/meta-llama/Llama-2-7b-hf", },
@ -103,7 +116,6 @@ models = [
{"name": "exaone", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct", }, {"name": "exaone", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct", },
{"name": "phi-2", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/microsoft/phi-2", }, {"name": "phi-2", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/microsoft/phi-2", },
{"name": "chameleon", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/facebook/chameleon-7b", }, {"name": "chameleon", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/facebook/chameleon-7b", },
{"name": "minerva-7b", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/sapienzanlp/Minerva-7B-base-v1.0", },
{"name": "roberta-bpe", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/sentence-transformers/stsb-roberta-base"}, {"name": "roberta-bpe", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/sentence-transformers/stsb-roberta-base"},
{"name": "gigachat", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/ai-sage/GigaChat-20B-A3B-instruct"}, {"name": "gigachat", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/ai-sage/GigaChat-20B-A3B-instruct"},
{"name": "megrez", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/Infinigence/Megrez-3B-Instruct"}, {"name": "megrez", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/Infinigence/Megrez-3B-Instruct"},
@ -114,11 +126,19 @@ models = [
{"name": "trillion", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/trillionlabs/Trillion-7B-preview", }, {"name": "trillion", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/trillionlabs/Trillion-7B-preview", },
{"name": "bailingmoe", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/inclusionAI/Ling-lite", }, {"name": "bailingmoe", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/inclusionAI/Ling-lite", },
{"name": "llama4", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/meta-llama/Llama-4-Scout-17B-16E-Instruct", }, {"name": "llama4", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/meta-llama/Llama-4-Scout-17B-16E-Instruct", },
{"name": "glm4", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/THUDM/glm-4-9b-hf", },
{"name": "pixtral", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/mistral-community/pixtral-12b", }, {"name": "pixtral", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/mistral-community/pixtral-12b", },
{"name": "seed-coder", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Base", }, {"name": "seed-coder", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Base", },
] ]
# some models are known to be broken upstream, so we will skip them as exceptions
pre_computed_hashes = [
# chatglm-bpe has 2 hashes, why?
{"name": "chatglm-bpe", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/THUDM/glm-4-9b-chat", "chkhsh": "b6e8e1518dc4305be2fe39c313ed643381c4da5db34a98f6a04c093f8afbe99b"},
{"name": "chatglm-bpe", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/THUDM/glm-4-9b-chat", "chkhsh": "81d72c7348a9f0ebe86f23298d37debe0a5e71149e29bd283904c02262b27516"},
{"name": "glm4", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/THUDM/glm-4-9b-hf", "chkhsh": "a1336059768a55c99a734006ffb02203cd450fed003e9a71886c88acf24fdbc2"},
{"name": "minerva-7b", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/sapienzanlp/Minerva-7B-base-v1.0", "chkhsh": "1431a23e583c97432bc230bff598d103ddb5a1f89960c8f1d1051aaa944d0b35"},
]
def download_file_with_auth(url, token, save_path): def download_file_with_auth(url, token, save_path):
headers = {"Authorization": f"Bearer {token}"} headers = {"Authorization": f"Bearer {token}"}
@ -169,9 +189,29 @@ def download_model(model):
if os.path.isfile(save_path): if os.path.isfile(save_path):
logger.info(f"{name}: File {save_path} already exists - skipping") logger.info(f"{name}: File {save_path} already exists - skipping")
continue continue
download_file_with_auth(f"{repo}/resolve/main/{file}", token, save_path) download_file_with_auth(f"{repo}/resolve/main/{file}", hf_token, save_path)
# get list of existing models and chkhsh from the convert_hf_to_gguf.py file
# returns mapping res --> chkhsh
def get_existing_models(convert_py):
pattern = r'if chkhsh == "([a-f0-9]{64})":\s*\n\s*.*\s*res = "([^"]+)"'
matches = re.findall(pattern, convert_py)
output = {}
for chkhsh, res in matches:
output[res] = chkhsh
return output
existing_models = {}
all_models = models.copy()
if not args.full:
# Filter out models that already exist in convert_hf_to_gguf.py
existing_models = get_existing_models(convert_py)
all_models = models.copy()
models = [model for model in all_models if model["name"] not in existing_models]
logging.info(f"Downloading {len(models)} models...")
for model in models: for model in models:
try: try:
download_model(model) download_model(model)
@ -182,9 +222,10 @@ for model in models:
# generate the source code for the convert_hf_to_gguf.py:get_vocab_base_pre() function: # generate the source code for the convert_hf_to_gguf.py:get_vocab_base_pre() function:
src_ifs = "" src_ifs = ""
for model in models: for model in [*all_models, *pre_computed_hashes]:
name = model["name"] name = model["name"]
tokt = model["tokt"] tokt = model["tokt"]
chkhsh = model.get("chkhsh")
if tokt == TOKENIZER_TYPE.SPM or tokt == TOKENIZER_TYPE.UGM: if tokt == TOKENIZER_TYPE.SPM or tokt == TOKENIZER_TYPE.UGM:
continue continue
@ -195,7 +236,16 @@ for model in models:
continue continue
# create the tokenizer # create the tokenizer
if chkhsh is not None:
# if the model has a pre-computed hash, use it
logger.info(f"Using pre-computed hash for model {name}: {chkhsh}")
elif name in existing_models:
# if the model already exists in convert_hf_to_gguf.py, skip compute hash
chkhsh = existing_models[name]
else:
# otherwise, compute the hash of the tokenizer
try: try:
logger.info(f"Loading tokenizer from {f'models/tokenizers/{name}'}...")
if name == "t5": if name == "t5":
tokenizer = AutoTokenizer.from_pretrained(f"models/tokenizers/{name}", use_fast=False) tokenizer = AutoTokenizer.from_pretrained(f"models/tokenizers/{name}", use_fast=False)
else: else:
@ -271,8 +321,6 @@ src_func = f"""
return res return res
""" """
convert_py_pth = pathlib.Path("convert_hf_to_gguf.py")
convert_py = convert_py_pth.read_text(encoding="utf-8")
convert_py = re.sub( convert_py = re.sub(
r"(# Marker: Start get_vocab_base_pre)(.+?)( +# Marker: End get_vocab_base_pre)", r"(# Marker: Start get_vocab_base_pre)(.+?)( +# Marker: End get_vocab_base_pre)",
lambda m: m.group(1) + src_func + m.group(3), lambda m: m.group(1) + src_func + m.group(3),
@ -367,6 +415,10 @@ for model in models:
logger.error(f"Failed to load tokenizer for model {name}. Error: {e}") logger.error(f"Failed to load tokenizer for model {name}. Error: {e}")
continue # Skip this model and continue with the next one in the loop continue # Skip this model and continue with the next one in the loop
if not os.path.exists(f"models/ggml-vocab-{name}.gguf"):
logger.info(f"Skip vocab files for model {name}, no GGUF file found")
continue
with open(f"models/ggml-vocab-{name}.gguf.inp", "w", encoding="utf-8") as f: with open(f"models/ggml-vocab-{name}.gguf.inp", "w", encoding="utf-8") as f:
for text in tests: for text in tests:
f.write(f"{text}") f.write(f"{text}")

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@ -1,6 +1,6 @@
ied 4 ½ months ied 4 ½ months
__ggml_vocab_test__ __ggml_vocab_test__
Führer Äpfel
__ggml_vocab_test__ __ggml_vocab_test__
__ggml_vocab_test__ __ggml_vocab_test__

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@ -1,5 +1,5 @@
29464 2094 1018 1092 2706 29464 2094 1018 1092 2706
11865 17875 9706 7959 2140

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@ -1,112 +0,0 @@
ied 4 ½ months
__ggml_vocab_test__
Führer
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
Hello world
__ggml_vocab_test__
Hello world
__ggml_vocab_test__
Hello World
__ggml_vocab_test__
Hello World
__ggml_vocab_test__
Hello World!
__ggml_vocab_test__
Hello, world!
__ggml_vocab_test__
Hello, world!
__ggml_vocab_test__
this is 🦙.cpp
__ggml_vocab_test__
w048 7tuijk dsdfhu
__ggml_vocab_test__
нещо на Български
__ggml_vocab_test__
កាន់តែពិសេសអាចខលចេញ
__ggml_vocab_test__
🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
Hello
__ggml_vocab_test__
(
__ggml_vocab_test__
=
__ggml_vocab_test__
' era
__ggml_vocab_test__
Hello, y'all! How are you 😁 ?我想在apple工作1314151天
__ggml_vocab_test__
!!!!!!
__ggml_vocab_test__
3
__ggml_vocab_test__
33
__ggml_vocab_test__
333
__ggml_vocab_test__
3333
__ggml_vocab_test__
33333
__ggml_vocab_test__
333333
__ggml_vocab_test__
3333333
__ggml_vocab_test__
33333333
__ggml_vocab_test__
333333333
__ggml_vocab_test__
Cửa Việt
__ggml_vocab_test__
discards
__ggml_vocab_test__
🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天 ------======= нещо на Български ''''''```````""""......!!!!!!?????? I've been 'told he's there, 'RE you sure? 'M not sure I'll make it, 'D you like some tea? We'Ve a'lL
__ggml_vocab_test__

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17245 16604 16403 16604 33583 18355
16421 51153
16604
16650
16650 16604
16581
16582
16582 16582
16582 16582 16582
16581 16582
31596 17394
34926 17394
31596 18671
34926 18671
34926 18671 16384
31596 16395 17394 16384
34926 16395 17394 16384
16811 16704 20410 16483 16631 16397 52854
16470 16399 16403 16407 16604 16406 35764 38185 51595 22592 26639
29479 23955 17012 20103 25527 27670 17408 19005 21473 24774
54254 42231 48084 29409 16617 61889 29409 16608 21954 16628 21954 16499 58445 29409 16607 58445 21954 16479 42231 21954 16611 21954 16607 21954 16633 21954 16611 29409 16607 21954 16615
52351 16604 16391 25825 16392 23686 16498 39161 18885 16618 16488 30853 16604 16391 54124 17153 25134 16656 18476 26169 16895 16392 62193 16611 16604 16391 24664 17153 57169 16721 16872 17073 17304 28729 16392
31596
34926
16650 31596
16650 34926
16696 31596
16696 31596 16582 16696 31596
16604 16391
16582 16604 16412
16390 22623
31596 16395 16712 16390 16828 16384 17674 16769 16732 23686 16607 16604 16414 24427 16623 41809 16495 28999 36469 45292 30197 16400 16402 16400 16403 16400 16404 16400 43969 65211 16636
16384 16384 16384 16384 16384 16384
16402
16402 16402
16402 16402 16402
16402 16402 16402 16402
16402 16402 16402 16402 16402
16402 16402 16402 16402 16402 16402
16402 16402 16402 16402 16402 16402 16402
16402 16402 16402 16402 16402 16402 16402 16402
16402 16402 16402 16402 16402 16402 16402 16402 16402
16418 19038 16639 16448 24315 33727 16467
18765 17981
16582 16604 16582 16582 16604 16582 16582 16582 16604 16581 16604 16581 16581 16604 16581 16582 16650 16582 16650 16604 16582 16696 16582 16696 16604 16582 52351 16604 16391 25825 16392 23686 16498 39161 18885 16618 16488 30853 16604 16391 54124 17153 25134 16656 18476 26169 16895 16392 62193 16611 20410 16483 16631 18885 16483 16631 16604 16402 16604 16402 16402 16604 16402 16402 16402 16604 16402 16402 16402 16402 16604 16402 16402 16402 16402 16402 16604 16402 16402 16402 16402 16402 16402 16604 16402 16402 16402 16402 16402 16402 16402 16604 16402 16402 16402 16402 16402 16402 16402 16402 16604 16402 16397 16402 16604 16402 16397 16397 16402 16604 16402 16397 16397 16397 16402 16604 54254 42231 48084 29409 16617 61889 29409 16608 21954 16628 21954 16499 58445 29409 16607 58445 21954 16479 42231 21954 16611 27683 16607 16604 16414 24427 16623 41809 16495 28999 36469 45292 30197 16400 16402 16400 16403 16400 16404 16400 43969 65211 16636 16604 16396 16396 16396 16396 16396 16396 16412 16412 16412 16412 16412 16412 16412 27268 23955 17012 20103 25527 27670 17408 19005 21473 24774 16604 16390 16390 16390 16390 16390 16390 16447 16447 16447 16447 16447 16447 16447 16385 16385 16385 16385 16397 16397 16397 16397 16397 16397 16384 16384 16384 16384 16384 16384 16414 16414 16414 16414 16414 16414 16687 16390 16690 16992 16604 16390 61797 16733 16390 16466 16986 16395 16604 16390 17879 16732 17811 16414 16604 16390 16428 16804 17811 16687 16390 16683 17190 16728 16395 16604 16390 16419 16732 16945 16991 25251 16414 17119 16390 38127 16641 16390 16459 16427

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ied 4 ½ months ied 4 ½ months
__ggml_vocab_test__ __ggml_vocab_test__
Führer Äpfel
__ggml_vocab_test__ __ggml_vocab_test__
__ggml_vocab_test__ __ggml_vocab_test__

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2536 228 27 228 22957 6983 2536 228 27 228 22957 6983
45 193433 90711 87 20910
228 228
1667 1667

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ied 4 ½ months ied 4 ½ months
__ggml_vocab_test__ __ggml_vocab_test__
Führer Äpfel
__ggml_vocab_test__ __ggml_vocab_test__
__ggml_vocab_test__ __ggml_vocab_test__

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1050 207 19 207 19192 4217 1050 207 19 207 19192 4217
37 32009 71 6247 125 213 26862 282
207 207
243 243

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ied 4 ½ months ied 4 ½ months
__ggml_vocab_test__ __ggml_vocab_test__
Führer Äpfel
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__ggml_vocab_test__ __ggml_vocab_test__

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1052 207 19 207 19109 4223 1052 207 19 207 19109 4223
37 100014 71 6245 82077 26723 282
207 207
243 243

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ied 4 ½ months
__ggml_vocab_test__
Führer
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__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
Hello world
__ggml_vocab_test__
Hello world
__ggml_vocab_test__
Hello World
__ggml_vocab_test__
Hello World
__ggml_vocab_test__
Hello World!
__ggml_vocab_test__
Hello, world!
__ggml_vocab_test__
Hello, world!
__ggml_vocab_test__
this is 🦙.cpp
__ggml_vocab_test__
w048 7tuijk dsdfhu
__ggml_vocab_test__
нещо на Български
__ggml_vocab_test__
កាន់តែពិសេសអាចខលចេញ
__ggml_vocab_test__
🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
Hello
__ggml_vocab_test__
(
__ggml_vocab_test__
=
__ggml_vocab_test__
' era
__ggml_vocab_test__
Hello, y'all! How are you 😁 ?我想在apple工作1314151天
__ggml_vocab_test__
!!!!!!
__ggml_vocab_test__
3
__ggml_vocab_test__
33
__ggml_vocab_test__
333
__ggml_vocab_test__
3333
__ggml_vocab_test__
33333
__ggml_vocab_test__
333333
__ggml_vocab_test__
3333333
__ggml_vocab_test__
33333333
__ggml_vocab_test__
333333333
__ggml_vocab_test__
Cửa Việt
__ggml_vocab_test__
discards
__ggml_vocab_test__
🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天 ------======= нещо на Български ''''''```````""""......!!!!!!?????? I've been 'told he's there, 'RE you sure? 'M not sure I'll make it, 'D you like some tea? We'Ve a'lL
__ggml_vocab_test__

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1122 220 19 220 26062 3951
37 50753 261
220
256
262
197
198
271
1406
1572
9707 1879
21927 1879
9707 4337
21927 4337
21927 4337 0
9707 11 1879 0
21927 11 1879 0
419 374 11162 99 247 13 10821
86 15 19 23 220 22 83 1963 41808 11472 2940 16739
78762 14144 1456 13073 63471 33594 3038 133178 79012
146394 97529 241 44258 233 146568 44258 224 147603 20879 115 146280 44258 223 146280 147272 97529 227 147805 148301 147270 44258 223 146848
145836 320 8252 8 26525 114 378 235 149921 30543 320 35673 99066 97534 8 25521 227 320 3243 42365 429 702 1181 1828 3950 8
9707
21927
220 21927
256 21927
262 21927
262 21927 198 262 21927
320
198 284
6 11385
9707 11 379 64848 0 2585 525 498 26525 223 937 104100 18493 22377 99257 16 18 16 19 16 20 16 35727 21216
17085 2928
18
18 18
18 18 18
18 18 18 18
18 18 18 18 18
18 18 18 18 18 18
18 18 18 18 18 18 18
18 18 18 18 18 18 18 18
18 18 18 18 18 18 18 18 18
34 90063 128324
2560 2347
198 4710 14731 65497 7847 1572 2303 78672 10947 145836 320 8252 8 26525 114 378 235 149921 30543 320 35673 99066 97534 8 25521 227 11162 99 247 149955 220 18 220 18 18 220 18 18 18 220 18 18 18 18 220 18 18 18 18 18 220 18 18 18 18 18 18 220 18 18 18 18 18 18 18 220 18 18 18 18 18 18 18 18 220 18 13 18 220 18 496 18 220 18 1112 18 220 146394 97529 241 44258 233 146568 44258 224 147603 20879 115 146280 44258 223 146280 147272 97529 227 144534 937 104100 18493 22377 99257 16 18 16 19 16 20 16 35727 21216 55460 53237 18658 14144 1456 13073 63471 33594 3038 133178 79012 3355 4605 4605 13874 13874 73594 3014 3014 28149 17085 2928 26610 7646 358 3003 1012 364 83 813 566 594 1052 11 364 787 498 2704 30 364 44 537 2704 358 3278 1281 432 11 364 35 498 1075 1045 15243 30 1205 6 42612 264 63866 43

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ied 4 ½ months ied 4 ½ months
__ggml_vocab_test__ __ggml_vocab_test__
Führer Äpfel
__ggml_vocab_test__ __ggml_vocab_test__
__ggml_vocab_test__ __ggml_vocab_test__

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878 204 31 3068 133 2137 878 204 31 3068 133 2137
28611 132 30042 34502 18614 286
204 204
258 258

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ied 4 ½ months ied 4 ½ months
__ggml_vocab_test__ __ggml_vocab_test__
Führer Äpfel
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__ggml_vocab_test__ __ggml_vocab_test__

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798 604 25208 1933 798 604 25208 1933
37 9116 71 11751 127 226 79 69 417
220 220
220 220 220 220

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ied 4 ½ months
__ggml_vocab_test__
Führer
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__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
Hello world
__ggml_vocab_test__
Hello world
__ggml_vocab_test__
Hello World
__ggml_vocab_test__
Hello World
__ggml_vocab_test__
Hello World!
__ggml_vocab_test__
Hello, world!
__ggml_vocab_test__
Hello, world!
__ggml_vocab_test__
this is 🦙.cpp
__ggml_vocab_test__
w048 7tuijk dsdfhu
__ggml_vocab_test__
нещо на Български
__ggml_vocab_test__
កាន់តែពិសេសអាចខលចេញ
__ggml_vocab_test__
🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
Hello
__ggml_vocab_test__
(
__ggml_vocab_test__
=
__ggml_vocab_test__
' era
__ggml_vocab_test__
Hello, y'all! How are you 😁 ?我想在apple工作1314151天
__ggml_vocab_test__
!!!!!!
__ggml_vocab_test__
3
__ggml_vocab_test__
33
__ggml_vocab_test__
333
__ggml_vocab_test__
3333
__ggml_vocab_test__
33333
__ggml_vocab_test__
333333
__ggml_vocab_test__
3333333
__ggml_vocab_test__
33333333
__ggml_vocab_test__
333333333
__ggml_vocab_test__
Cửa Việt
__ggml_vocab_test__
discards
__ggml_vocab_test__
🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天 ------======= нещо на Български ''''''```````""""......!!!!!!?????? I've been 'told he's there, 'RE you sure? 'M not sure I'll make it, 'D you like some tea? We'Ve a'lL
__ggml_vocab_test__

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1165 220 19 220 27124 5503
37 19194 259
220
256
271
197
198
279
2499
2775
13225 2375
32949 2375
13225 5922
32949 5922
32949 5922 0
13225 11 2375 0
32949 11 2375 0
495 382 9552 99 247 13 17159
86 45404 220 22 10191 2852 22924 4750 6916
3907 53641 1235 185386 8118
11400 107516 15867 20804 22851 134178 77431 32010 104312 37984 16329 27751 89335
112927 222 350 14559 8 22861 114 2524 64364 104 15148 350 76466 166700 121942 780 8 91349 350 7393 74471 484 853 1617 2316 6602 8
13225
32949
220 32949
256 32949
271 32949
271 32949 198 271 32949
350
198 314
6 6837
13225 11 342 70653 0 3253 553 481 22861 223 1423 7522 18165 2178 34058 22369 16412 32999 16 867 8208
147475
18
2546
15517
15517 18
15517 2546
15517 15517
15517 15517 18
15517 15517 2546
15517 15517 15517
34 60213 53904
2960 3098
126470 25980 160432 16609 2775 4066 172261 19432 112927 222 350 14559 8 22861 114 2524 64364 104 15148 350 76466 166700 121942 780 8 91349 9552 99 247 4103 99 247 220 18 220 2546 220 15517 220 15517 18 220 15517 2546 220 15517 15517 220 15517 15517 18 220 15517 15517 2546 220 18 13 18 220 18 485 18 220 18 1008 18 44735 107516 15867 20804 22851 134178 77431 32010 104312 156437 1423 7522 18165 2178 34058 22369 16412 32999 16 867 8208 105024 106657 1967 53641 1235 185386 8118 22434 39336 26178 26178 168394 194663 27271 147475 25883 6961 9790 1339 461 83 1280 19016 1354 11 461 1099 481 3239 30 461 44 625 3239 17291 1520 480 11 461 35 481 1299 1236 17966 30 1416 6 27493 261 54602 43

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__ggml_vocab_test__ __ggml_vocab_test__
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__ggml_vocab_test__ __ggml_vocab_test__
__ggml_vocab_test__ __ggml_vocab_test__

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1142 220 19 220 27154 4038 1142 220 19 220 27154 4038
37 51853 261 88075 16276 301
220 220
256 256

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__ggml_vocab_test__ __ggml_vocab_test__
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__ggml_vocab_test__ __ggml_vocab_test__

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474 287 29871 29946 29871 30226 7378 474 287 29871 29946 29871 30226 7378
383 4000 261 11585 7810 295
259 259
1678 1678

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ied 4 ½ months
__ggml_vocab_test__
Führer
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__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
Hello world
__ggml_vocab_test__
Hello world
__ggml_vocab_test__
Hello World
__ggml_vocab_test__
Hello World
__ggml_vocab_test__
Hello World!
__ggml_vocab_test__
Hello, world!
__ggml_vocab_test__
Hello, world!
__ggml_vocab_test__
this is 🦙.cpp
__ggml_vocab_test__
w048 7tuijk dsdfhu
__ggml_vocab_test__
нещо на Български
__ggml_vocab_test__
កាន់តែពិសេសអាចខលចេញ
__ggml_vocab_test__
🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
Hello
__ggml_vocab_test__
(
__ggml_vocab_test__
=
__ggml_vocab_test__
' era
__ggml_vocab_test__
Hello, y'all! How are you 😁 ?我想在apple工作1314151天
__ggml_vocab_test__
!!!!!!
__ggml_vocab_test__
3
__ggml_vocab_test__
33
__ggml_vocab_test__
333
__ggml_vocab_test__
3333
__ggml_vocab_test__
33333
__ggml_vocab_test__
333333
__ggml_vocab_test__
3333333
__ggml_vocab_test__
33333333
__ggml_vocab_test__
333333333
__ggml_vocab_test__
Cửa Việt
__ggml_vocab_test__
discards
__ggml_vocab_test__
🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天 ------======= нещо на Български ''''''```````""""......!!!!!!?????? I've been 'told he's there, 'RE you sure? 'M not sure I'll make it, 'D you like some tea? We'Ve a'lL
__ggml_vocab_test__

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1190 220 32 220 18215 7112
50 16800 258
220
256
277
197
198
368
2946
3271
19873 3817
39715 3817
19873 7353
39715 7353
39715 7353 13
19873 24 3817 13
39715 24 3817 13
544 373 9522 112 247 26 36315
99 39923 220 35 9607 21498 21470 3679 9433
1595 7653 633 79829 34051 1636
8755 102595 115960 21125 148305 96819 102816 39048 14105 22528 160234
114590 222 330 14879 21 51358 127 12817 93293 117 24204 330 68239 881 120327 170428 21 89101 330 7384 88230 511 947 1492 3742 7233 21
19873
39715
220 39715
256 39715
277 39715
277 39715 198 277 39715
330
198 319
19 7359
19873 24 386 87799 13 2403 583 650 51358 223 1663 155736 1522 42056 7544 13336 28785 29 4412 20645
17931 4959
31
1922
12325
12325 31
12325 1922
12325 12325
12325 12325 31
12325 12325 1922
12325 12325 12325
47 19811 12077
3260 3579
198 7283 51499 191231 20192 3271 3322 9287 2143 17860 114590 222 330 14879 21 51358 127 12817 93293 117 24204 330 68239 881 120327 170428 21 89101 9522 112 247 172394 247 220 31 220 1922 220 12325 220 12325 31 220 12325 1922 220 12325 12325 220 12325 12325 31 220 12325 12325 1922 220 31 26 31 220 31 396 31 220 31 1043 31 117131 102595 115960 21125 148305 96819 102816 80883 223 1663 155736 1522 42056 7544 13336 28785 29 4412 20645 79745 150278 117079 633 79829 34051 1636 25611 41990 109428 1488 91054 24072 17931 4959 29795 9296 16517 1806 481 96 1386 36633 1609 24 481 1109 650 5074 43 481 57 702 5074 27088 2170 536 24 481 48 650 1933 1696 30262 43 1665 19 32818 262 27236 56

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__ggml_vocab_test__ __ggml_vocab_test__
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__ggml_vocab_test__ __ggml_vocab_test__

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728 577 24142 2607 728 577 24142 2607
39 26288 6554 37515 18569 293
209 209
50276 50276

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ied 4 ½ months
__ggml_vocab_test__
Führer
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__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
Hello world
__ggml_vocab_test__
Hello world
__ggml_vocab_test__
Hello World
__ggml_vocab_test__
Hello World
__ggml_vocab_test__
Hello World!
__ggml_vocab_test__
Hello, world!
__ggml_vocab_test__
Hello, world!
__ggml_vocab_test__
this is 🦙.cpp
__ggml_vocab_test__
w048 7tuijk dsdfhu
__ggml_vocab_test__
нещо на Български
__ggml_vocab_test__
កាន់តែពិសេសអាចខលចេញ
__ggml_vocab_test__
🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
Hello
__ggml_vocab_test__
(
__ggml_vocab_test__
=
__ggml_vocab_test__
' era
__ggml_vocab_test__
Hello, y'all! How are you 😁 ?我想在apple工作1314151天
__ggml_vocab_test__
!!!!!!
__ggml_vocab_test__
3
__ggml_vocab_test__
33
__ggml_vocab_test__
333
__ggml_vocab_test__
3333
__ggml_vocab_test__
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33333333
__ggml_vocab_test__
333333333
__ggml_vocab_test__
Cửa Việt
__ggml_vocab_test__
discards
__ggml_vocab_test__
🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天 ------======= нещо на Български ''''''```````""""......!!!!!!?????? I've been 'told he's there, 'RE you sure? 'M not sure I'll make it, 'D you like some tea? We'Ve a'lL
__ggml_vocab_test__

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17 297 201 78660 21775
72805 4097 56
35378 8999
35378 8999
35378 6661
35378 6661
35378 6661 38
35378 4 8999 38
35378 4 8999 38
903 83 6 3 5 238 6366
148 7709 1019 361 458 134362 104 7 71 420 1132
14271 29 117152
6 149561 78270 48967 64254 7616 81705
6 247206 15 33176 16 6 247442 6 3 15755 15 144227 8705 18255 40292 158 4460 33 27686 16 6 142325 15 191 538 28 121505 450 1556 6863 10002 47 1098 16
35378
35378
35378
35378
35378
35378 35378
15
2203
242 1615
35378 4 113 25 5584 38 11249 621 398 6 201344 705 23638 213 9007 133 1879 2681 2592 135224 1906 6087
6 90827
138
3912
6 66000
138 66000
3912 66000
6 66000 66000
138 66000 66000
3912 66000 66000
6 66000 66000 66000
199152 3763
17116 99397
6 247206 15 33176 16 6 247442 6 3 15755 15 144227 8705 18255 40292 158 4460 33 27686 16 6 142325 6 3 138 3912 6 66000 138 66000 3912 66000 6 66000 66000 138 66000 66000 3912 66000 66000 80308 1031 5 363 138 27 363 6 149561 78270 48967 201344 705 23638 213 9007 133 1879 2681 2592 135224 1906 6087 6 110405 1369 69112 69112 69112 14271 29 117152 5106 4765 4765 1135 164721 164721 164721 58 58 58 58 2551 90827 32 85908 87 25 272 2809 242 18 18345 764 25 7 2685 4 242 11766 398 9077 32 242 594 959 9077 87 25 1181 3249 442 4 242 397 398 1884 3060 26156 32 1401 25 26455 10 25 141 866

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ied 4 ½ months ied 4 ½ months
__ggml_vocab_test__ __ggml_vocab_test__
Führer Äpfel
__ggml_vocab_test__ __ggml_vocab_test__
__ggml_vocab_test__ __ggml_vocab_test__

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259 259
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ied 4 ½ months
__ggml_vocab_test__
Führer
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
Hello world
__ggml_vocab_test__
Hello world
__ggml_vocab_test__
Hello World
__ggml_vocab_test__
Hello World
__ggml_vocab_test__
Hello World!
__ggml_vocab_test__
Hello, world!
__ggml_vocab_test__
Hello, world!
__ggml_vocab_test__
this is 🦙.cpp
__ggml_vocab_test__
w048 7tuijk dsdfhu
__ggml_vocab_test__
нещо на Български
__ggml_vocab_test__
កាន់តែពិសេសអាចខលចេញ
__ggml_vocab_test__
🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
Hello
__ggml_vocab_test__
(
__ggml_vocab_test__
=
__ggml_vocab_test__
' era
__ggml_vocab_test__
Hello, y'all! How are you 😁 ?我想在apple工作1314151天
__ggml_vocab_test__
!!!!!!
__ggml_vocab_test__
3
__ggml_vocab_test__
33
__ggml_vocab_test__
333
__ggml_vocab_test__
3333
__ggml_vocab_test__
33333
__ggml_vocab_test__
333333
__ggml_vocab_test__
3333333
__ggml_vocab_test__
33333333
__ggml_vocab_test__
333333333
__ggml_vocab_test__
Cửa Việt
__ggml_vocab_test__
discards
__ggml_vocab_test__
🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天 ------======= нещо на Български ''''''```````""""......!!!!!!?????? I've been 'told he's there, 'RE you sure? 'M not sure I'll make it, 'D you like some tea? We'Ve a'lL
__ggml_vocab_test__

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2014 1032 1052 1032 28504 6972
1070 7088 1258
1032
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22177 4304
45383 4304
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22177 1044 4304 1033
45383 1044 4304 1033
1593 1395 119685 1166 1153 1046 51228
1119 1048 1052 1056 1032 1055 17391 23216 30203 7785 17279
3337 30757 1902 4200 63073 3671
1225 1158 1128 1225 1158 1182 1225 1158 1147 1225 1159 1139 1225 1158 1143 1225 1159 1130 1225 1158 1150 1225 1158 1183 1225 1158 1159 1225 21359 1225 1158 1159 1225 1158 1162 1225 1158 1182 1225 1158 1133 1225 1158 1129 1225 1158 1155 1225 1158 1133 1225 21359 1225 1158 1137
1240 1159 1154 1128 1319 13052 1041 119685 1152 1182 29568 1240 1159 1140 1171 1239 1184 1143 1319 88181 1873 3659 1275 56421 1621 1041 126241 1133 1319 11234 1873 26303 1455 1934 2246 3754 10835 1041
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7290 7290 7290
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1067 59503 28783
3724 4058
1010 1032 1267 1032 4688 1032 17152 1458 29356 1010 1256 1010 1293 1010 1260 1010 1652 1010 1240 1159 1154 1128 1319 13052 1041 119685 1152 1182 29568 1240 1159 1140 1171 1239 1184 1143 1319 88181 1873 3659 1275 56421 1621 1041 126241 1133 119685 1166 1153 1240 1159 1166 1153 1032 1051 1032 1051 1051 1032 1051 1051 1051 1032 1051 1051 1051 1051 1032 1051 1051 1051 1051 1051 1032 1051 1051 1051 1051 1051 1051 1032 1051 1051 1051 1051 1051 1051 1051 1032 1051 1051 1051 1051 1051 1051 1051 1051 1032 1051 1046 1051 1032 1051 1791 1051 1032 1051 2880 1051 71881 1158 1128 1225 1158 1182 1225 1158 1147 1225 1159 1139 1225 1158 1143 1225 1159 1130 1225 1158 1150 1225 1158 1183 1225 1158 1159 1225 21359 1225 1158 1159 1225 1158 1162 1225 1158 1182 1225 1158 1133 1240 1159 1152 1129 3082 26060 2998 63614 82278 1049 1051 1049 1052 1049 1053 1049 6434 6749 45577 1045 6626 43555 2843 30757 1902 4200 63073 3671 14931 20040 20040 1657 1657 1975 14135 14135 83923 7290 7290 7290 45509 45509 45509 1362 6483 2151 1576 1116 2189 1514 1681 2156 1044 1576 3609 1636 5257 1063 1576 1077 1605 5257 1362 7534 3180 1494 1044 1576 1068 1636 2479 2269 26883 1063 2837 1039 45654 1261 54297 1076

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ied 4 ½ months ied 4 ½ months
__ggml_vocab_test__ __ggml_vocab_test__
Führer Äpfel
__ggml_vocab_test__ __ggml_vocab_test__
__ggml_vocab_test__ __ggml_vocab_test__

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37 50753 261 86975 15897 301
220 220
256 256

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ied 4 ½ months ied 4 ½ months
__ggml_vocab_test__ __ggml_vocab_test__
Führer Äpfel
__ggml_vocab_test__ __ggml_vocab_test__
__ggml_vocab_test__ __ggml_vocab_test__

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4833 225 38 225 143 140 17723 4833 225 38 225 143 140 17723
56 2006 3935 265 144 231 7132 342
225 225
261 261

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@ -1,112 +0,0 @@
ied 4 ½ months
__ggml_vocab_test__
Führer
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
__ggml_vocab_test__
Hello world
__ggml_vocab_test__
Hello world
__ggml_vocab_test__
Hello World
__ggml_vocab_test__
Hello World
__ggml_vocab_test__
Hello World!
__ggml_vocab_test__
Hello, world!
__ggml_vocab_test__
Hello, world!
__ggml_vocab_test__
this is 🦙.cpp
__ggml_vocab_test__
w048 7tuijk dsdfhu
__ggml_vocab_test__
нещо на Български
__ggml_vocab_test__
កាន់តែពិសេសអាចខលចេញ
__ggml_vocab_test__
🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
__ggml_vocab_test__
Hello
Hello
__ggml_vocab_test__
(
__ggml_vocab_test__
=
__ggml_vocab_test__
' era
__ggml_vocab_test__
Hello, y'all! How are you 😁 ?我想在apple工作1314151天
__ggml_vocab_test__
!!!!!!
__ggml_vocab_test__
3
__ggml_vocab_test__
33
__ggml_vocab_test__
333
__ggml_vocab_test__
3333
__ggml_vocab_test__
33333
__ggml_vocab_test__
333333
__ggml_vocab_test__
3333333
__ggml_vocab_test__
33333333
__ggml_vocab_test__
333333333
__ggml_vocab_test__
Cửa Việt
__ggml_vocab_test__
discards
__ggml_vocab_test__
🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天 ------======= нещо на Български ''''''```````""""......!!!!!!?????? I've been 'told he's there, 'RE you sure? 'M not sure I'll make it, 'D you like some tea? We'Ve a'lL
__ggml_vocab_test__

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2550 204 18430 377
597 2768 298 8564
1437
1437 1437
1437 1437 1437
50117
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50140
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50117 50118
31414 232
20920 232
31414 623
20920 623
20920 623 328
31414 6 232 328
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42 16 8103 18164 27 4 49317
605 40976 262 10109 18474 385 29 36807 6455
36765 25482 22063 23171 34251 18697 10809 26161 18697 3602 22063 27969 40966 25417 15264 26161 24269 36709 41171 35328
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ied 4 ½ months ied 4 ½ months
__ggml_vocab_test__ __ggml_vocab_test__
Führer Äpfel
__ggml_vocab_test__ __ggml_vocab_test__
__ggml_vocab_test__ __ggml_vocab_test__

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@ -92,12 +92,14 @@ llama_test(test-tokenizer-0 NAME test-tokenizer-0-gpt-2 ARGS ${CMAKE
llama_test(test-tokenizer-0 NAME test-tokenizer-0-llama-bpe ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama-bpe.gguf) llama_test(test-tokenizer-0 NAME test-tokenizer-0-llama-bpe ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama-bpe.gguf)
llama_test(test-tokenizer-0 NAME test-tokenizer-0-llama-spm ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama-spm.gguf) llama_test(test-tokenizer-0 NAME test-tokenizer-0-llama-spm ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama-spm.gguf)
llama_test(test-tokenizer-0 NAME test-tokenizer-0-mpt ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-mpt.gguf) llama_test(test-tokenizer-0 NAME test-tokenizer-0-mpt ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-mpt.gguf)
llama_test(test-tokenizer-0 NAME test-tokenizer-0-nomic-bert-moe ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-nomic-bert-moe.gguf)
llama_test(test-tokenizer-0 NAME test-tokenizer-0-phi-3 ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-phi-3.gguf) llama_test(test-tokenizer-0 NAME test-tokenizer-0-phi-3 ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-phi-3.gguf)
llama_test(test-tokenizer-0 NAME test-tokenizer-0-qwen2 ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-qwen2.gguf) llama_test(test-tokenizer-0 NAME test-tokenizer-0-qwen2 ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-qwen2.gguf)
llama_test(test-tokenizer-0 NAME test-tokenizer-0-refact ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-refact.gguf) llama_test(test-tokenizer-0 NAME test-tokenizer-0-refact ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-refact.gguf)
llama_test(test-tokenizer-0 NAME test-tokenizer-0-starcoder ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-starcoder.gguf) llama_test(test-tokenizer-0 NAME test-tokenizer-0-starcoder ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-starcoder.gguf)
# TODO: missing HF tokenizer for this model in convert_hf_to_gguf_update.py, see https://github.com/ggml-org/llama.cpp/pull/13847
# llama_test(test-tokenizer-0 NAME test-tokenizer-0-nomic-bert-moe ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-nomic-bert-moe.gguf)
if (LLAMA_LLGUIDANCE) if (LLAMA_LLGUIDANCE)
llama_build_and_test(test-grammar-llguidance.cpp ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama-bpe.gguf) llama_build_and_test(test-grammar-llguidance.cpp ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama-bpe.gguf)
endif () endif ()