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* server : (experimental) vision support via libmtmd * mtmd : add more api around mtmd_image_tokens * mtmd : add more api around mtmd_image_tokens * mtmd : ability to calc image hash * shared_ptr for mtmd_image_tokens * move hash to user-define ID (fixed) * abstract out the batch management * small fix * refactor logic adding tokens to batch * implement hashing image * use FNV hash, now hash bitmap instead of file data * allow decoding image embedding to be split into batches * rm whitespace * disable some features when mtmd is on * fix --no-mmproj-offload * mtmd_context_params no timings * refactor server_inp to server_tokens * fix the failing test case * init * wip * working version * add mtmd::bitmaps * add test target * rm redundant define * test: mtmd_input_chunks_free * rm outdated comment * fix merging issue * explicitly create mtmd::input_chunks * mtmd_input_chunk_copy * add clone() * improve server_input struct * clip : fix confused naming ffn_up and ffn_down * rm ffn_i/o/g naming * rename n_embd, n_ff * small fix * no check n_ff * fix detokenize * add const to various places * add warning about breaking changes * add c api * helper: use mtmd_image_tokens_get_n_pos * fix ctx_shift * fix name shadowing * more strict condition * support remote image_url * remote image_url log * add CI test * do not log base64 * add "has_multimodal" to /props * remove dangling image * speculative: use slot.cache_tokens.insert * Apply suggestions from code review Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * rm can_be_detokenized * on prmpt processing done, assert cache_tokens.size * handle_completions_impl returns void * adapt the new web ui * update docs and hot topics * rm assert * small fix (2) --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
62 lines
4.9 KiB
Markdown
62 lines
4.9 KiB
Markdown
# Multimodal Support in llama.cpp
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This directory provides multimodal capabilities for `llama.cpp`. Initially intended as a showcase for running LLaVA models, its scope has expanded significantly over time to include various other vision-capable models. As a result, LLaVA is no longer the only multimodal architecture supported.
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> [!IMPORTANT]
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>
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> Multimodal support can be viewed as a sub-project within `llama.cpp`. It is under **very heavy development**, and **breaking changes are expected**.
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The naming and structure related to multimodal support have evolved, which might cause some confusion. Here's a brief timeline to clarify:
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- [#3436](https://github.com/ggml-org/llama.cpp/pull/3436): Initial support for LLaVA 1.5 was added, introducing `llava.cpp` and `clip.cpp`. The `llava-cli` binary was created for model interaction.
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- [#4954](https://github.com/ggml-org/llama.cpp/pull/4954): Support for MobileVLM was added, becoming the second vision model supported. This built upon the existing `llava.cpp`, `clip.cpp`, and `llava-cli` infrastructure.
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- **Expansion & Fragmentation:** Many new models were subsequently added (e.g., [#7599](https://github.com/ggml-org/llama.cpp/pull/7599), [#10361](https://github.com/ggml-org/llama.cpp/pull/10361), [#12344](https://github.com/ggml-org/llama.cpp/pull/12344), and others). However, `llava-cli` lacked support for the increasingly complex chat templates required by these models. This led to the creation of model-specific binaries like `qwen2vl-cli`, `minicpmv-cli`, and `gemma3-cli`. While functional, this proliferation of command-line tools became confusing for users.
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- [#12849](https://github.com/ggml-org/llama.cpp/pull/12849): `libmtmd` was introduced as a replacement for `llava.cpp`. Its goals include providing a single, unified command-line interface, improving the user/developer experience (UX/DX), and supporting both audio and image inputs.
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- [#13012](https://github.com/ggml-org/llama.cpp/pull/13012): `mtmd-cli` was added, consolidating the various model-specific CLIs into a single tool powered by `libmtmd`.
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## Pre-quantized models
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See the list of pre-quantized model [here](../../docs/multimodal.md)
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## How it works and what is `mmproj`?
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Multimodal support in `llama.cpp` works by encoding images into embeddings using a separate model component, and then feeding these embeddings into the language model.
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This approach keeps the multimodal components distinct from the core `libllama` library. Separating these allows for faster, independent development cycles. While many modern vision models are based on Vision Transformers (ViTs), their specific pre-processing and projection steps can vary significantly. Integrating this diverse complexity directly into `libllama` is currently challenging.
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Consequently, running a multimodal model typically requires two GGUF files:
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1. The standard language model file.
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2. A corresponding **multimodal projector (`mmproj`)** file, which handles the image encoding and projection.
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## What is `libmtmd`?
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As outlined in the history, `libmtmd` is the modern library designed to replace the original `llava.cpp` implementation for handling multimodal inputs.
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Built upon `clip.cpp` (similar to `llava.cpp`), `libmtmd` offers several advantages:
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- **Unified Interface:** Aims to consolidate interaction for various multimodal models.
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- **Improved UX/DX:** Features a more intuitive API, inspired by the `Processor` class in the Hugging Face `transformers` library.
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- **Flexibility:** Designed to support multiple input types (text, audio, images) while respecting the wide variety of chat templates used by different models.
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## How to obtain `mmproj`
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Multimodal projector (`mmproj`) files are specific to each model architecture.
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For the following models, you can use `convert_hf_to_gguf.py`with `--mmproj` flag to get the `mmproj` file:
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- [Gemma 3](https://huggingface.co/collections/google/gemma-3-release-67c6c6f89c4f76621268bb6d) - Note: 1B variant does not have vision support
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- SmolVLM (from [HuggingFaceTB](https://huggingface.co/HuggingFaceTB))
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- SmolVLM2 (from [HuggingFaceTB](https://huggingface.co/HuggingFaceTB))
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- [Pixtral 12B](https://huggingface.co/mistral-community/pixtral-12b) - only works with `transformers`-compatible checkpoint
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- Qwen 2 VL and Qwen 2.5 VL (from [Qwen](https://huggingface.co/Qwen))
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- [Mistral Small 3.1 24B](https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503)
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For older models, please refer to the relevant guide for instructions on how to obtain or create them:
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- [LLaVA](../../docs/multimodal/llava.md)
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- [MobileVLM](../../docs/multimodal/MobileVLM.md)
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- [GLM-Edge](../../docs/multimodal/glmedge.md)
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- [MiniCPM-V 2.5](../../docs/multimodal/minicpmv2.5.md)
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- [MiniCPM-V 2.6](../../docs/multimodal/minicpmv2.6.md)
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- [MiniCPM-o 2.6](../../docs/multimodal/minicpmo2.6.md)
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- [IBM Granite Vision](../../docs/multimodal/granitevision.md)
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- [Google Gemma 3](../../docs/multimodal/gemma3.md)
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