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* wip llama 4 conversion * rm redundant __init__ * fix conversion * fix conversion * test impl * try this * reshape patch_embeddings_0 * fix view * rm ffn_post_norm * cgraph ok * f32 for pos embd * add image marker tokens * Llama4UnfoldConvolution * correct pixel shuffle * fix merge conflicts * correct * add debug_graph * logits matched, but it still preceives the image incorrectly * fix style * add image_grid_pinpoints * handle llama 4 preprocessing * rm load_image_size * rm unused line * fix * small fix 2 * add test & docs * fix llava-1.6 test * test: add notion of huge models * add comment * add warn about degraded quality
81 lines
2.9 KiB
Markdown
81 lines
2.9 KiB
Markdown
# Multimodal
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llama.cpp supports multimodal input via `libmtmd`. Currently, there are 2 tools support this feature:
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- [llama-mtmd-cli](../tools/mtmd/README.md)
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- [llama-server](../tools/server/README.md) via OpenAI-compatible `/chat/completions` API
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To enable it, can use use one of the 2 methods below:
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- Use `-hf` option with a supported model (see a list of pre-quantized model below)
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- To load a model using `-hf` while disabling multimodal, use `--no-mmproj`
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- To load a model using `-hf` while using a custom mmproj file, use `--mmproj local_file.gguf`
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- Use `-m model.gguf` option with `--mmproj file.gguf` to specify text and multimodal projector respectively
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By default, multimodal projector will be offloaded to GPU. To disable this, add `--no-mmproj-offload`
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For example:
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```sh
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# simple usage with CLI
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llama-mtmd-cli -hf ggml-org/gemma-3-4b-it-GGUF
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# simple usage with server
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llama-server -hf ggml-org/gemma-3-4b-it-GGUF
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# using local file
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llama-server -m gemma-3-4b-it-Q4_K_M.gguf --mmproj mmproj-gemma-3-4b-it-Q4_K_M.gguf
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# no GPU offload
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llama-server -hf ggml-org/gemma-3-4b-it-GGUF --no-mmproj-offload
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```
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## Pre-quantized models
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These are ready-to-use models, most of them come with `Q4_K_M` quantization by default. They can be found at the Hugging Face page of the ggml-org: https://huggingface.co/ggml-org
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Replaces the `(tool_name)` with the name of binary you want to use. For example, `llama-mtmd-cli` or `llama-server`
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NOTE: some models may require large context window, for example: `-c 8192`
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```sh
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# Gemma 3
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(tool_name) -hf ggml-org/gemma-3-4b-it-GGUF
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(tool_name) -hf ggml-org/gemma-3-12b-it-GGUF
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(tool_name) -hf ggml-org/gemma-3-27b-it-GGUF
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# SmolVLM
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(tool_name) -hf ggml-org/SmolVLM-Instruct-GGUF
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(tool_name) -hf ggml-org/SmolVLM-256M-Instruct-GGUF
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(tool_name) -hf ggml-org/SmolVLM-500M-Instruct-GGUF
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(tool_name) -hf ggml-org/SmolVLM2-2.2B-Instruct-GGUF
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(tool_name) -hf ggml-org/SmolVLM2-256M-Video-Instruct-GGUF
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(tool_name) -hf ggml-org/SmolVLM2-500M-Video-Instruct-GGUF
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# Pixtral 12B
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(tool_name) -hf ggml-org/pixtral-12b-GGUF
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# Qwen 2 VL
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(tool_name) -hf ggml-org/Qwen2-VL-2B-Instruct-GGUF
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(tool_name) -hf ggml-org/Qwen2-VL-7B-Instruct-GGUF
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# Qwen 2.5 VL
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(tool_name) -hf ggml-org/Qwen2.5-VL-3B-Instruct-GGUF
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(tool_name) -hf ggml-org/Qwen2.5-VL-7B-Instruct-GGUF
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(tool_name) -hf ggml-org/Qwen2.5-VL-32B-Instruct-GGUF
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(tool_name) -hf ggml-org/Qwen2.5-VL-72B-Instruct-GGUF
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# Mistral Small 3.1 24B (IQ2_M quantization)
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(tool_name) -hf ggml-org/Mistral-Small-3.1-24B-Instruct-2503-GGUF
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# InternVL 2.5 and 3
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(tool_name) -hf ggml-org/InternVL2_5-1B-GGUF
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(tool_name) -hf ggml-org/InternVL2_5-4B-GGUF
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(tool_name) -hf ggml-org/InternVL3-1B-Instruct-GGUF
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(tool_name) -hf ggml-org/InternVL3-2B-Instruct-GGUF
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(tool_name) -hf ggml-org/InternVL3-8B-Instruct-GGUF
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(tool_name) -hf ggml-org/InternVL3-14B-Instruct-GGUF
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# Llama 4 Scout
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(tool_name) -hf ggml-org/Llama-4-Scout-17B-16E-Instruct-GGUF
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```
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