c1c7026b47
Fix python stuff ( #109 )
2023-03-19 19:33:18 +02:00
467b149761
Refactoring convert-pth-to-ggml.py: more concise and readable ( #109 )
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* Refactor get_n_parts function to simplify code and improve readability
* Use f-strings instead of concatenation
* Refactoring: more concise and readable
* modularize
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Co-authored-by: Georgi Gerganov <ggerganov@gmail.com >
2023-03-19 19:17:39 +02:00
2af23d3043
🚀 Dockerize llamacpp ( #132 )
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* feat: dockerize llamacpp
* feat: split build & runtime stages
* split dockerfile into main & tools
* add quantize into tool docker image
* Update .devops/tools.sh
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com >
* add docker action pipeline
* change CI to publish at github docker registry
* fix name runs-on macOS-latest is macos-latest (lowercase)
* include docker versioned images
* fix github action docker
* fix docker.yml
* feat: include all-in-one command tool & update readme.md
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Co-authored-by: Georgi Gerganov <ggerganov@gmail.com >
2023-03-17 10:47:06 +01:00
956dfda8ad
Use tokenizer.vocab_size() instead of hardcoding 32000 in convert-pth-to-ggml.py ( #142 )
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There are ways that special tokens or other new tokens could be added to the tokenizer; therefore it's probably best not to assume the vocabulary is only 32000 tokens.
2023-03-15 21:37:50 +02:00
2a20f48efa
Fix UTF-8 handling (including colors) ( #79 )
2023-03-13 18:24:18 +02:00
7c9e54e55e
Revert "weights_only" arg - this causing more trouble than help
2023-03-12 20:59:01 +02:00
b9bd1d0141
python/pytorch compat notes ( #44 )
2023-03-12 14:16:33 +02:00
a93120236f
use weights_only in conversion script ( #32 )
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this restricts malicious weights from executing arbitrary code by restricting the unpickler to only loading tensors, primitive types, and dictionaries
2023-03-12 08:36:35 +02:00
007a8f6f45
Support all LLaMA models + change Q4_0 quantization storage
2023-03-11 11:28:30 +02:00
70bc0b8b15
Fix a bug in the rope calculation
2023-03-10 23:46:57 +02:00
26c0846629
Initial release
2023-03-10 20:56:40 +02:00
