| --- |
| datasets: |
| - Lin-Chen/ShareGPT4V |
| pipeline_tag: image-to-text |
| --- |
| |
| # MoMonir/llava-llama-3-8b-v1_1-GGUF |
| This model was converted to GGUF format from [`xtuner/llava-llama-3-8b-v1_1`](https://huggingface.co/xtuner/llava-llama-3-8b-v1_1) |
| Refer to the [original model card](https://huggingface.co/xtuner/llava-llama-3-8b-v1_1) for more details on the model. |
| |
| <!-- README_GGUF.md-about-gguf start --> |
| ### About GGUF ([TheBloke](https://huggingface.co/TheBloke) Description) |
|
|
| GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp. |
|
|
| Here is an incomplete list of clients and libraries that are known to support GGUF: |
|
|
| * [llama.cpp](https://github.com/ggerganov/llama.cpp). The source project for GGUF. Offers a CLI and a server option. |
| * [text-generation-webui](https://github.com/oobabooga/text-generation-webui), the most widely used web UI, with many features and powerful extensions. Supports GPU acceleration. |
| * [KoboldCpp](https://github.com/LostRuins/koboldcpp), a fully featured web UI, with GPU accel across all platforms and GPU architectures. Especially good for story telling. |
| * [GPT4All](https://gpt4all.io/index.html), a free and open source local running GUI, supporting Windows, Linux and macOS with full GPU accel. |
| * [LM Studio](https://lmstudio.ai/), an easy-to-use and powerful local GUI for Windows and macOS (Silicon), with GPU acceleration. Linux available, in beta as of 27/11/2023. |
| * [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui), a great web UI with many interesting and unique features, including a full model library for easy model selection. |
| * [Faraday.dev](https://faraday.dev/), an attractive and easy to use character-based chat GUI for Windows and macOS (both Silicon and Intel), with GPU acceleration. |
| * [llama-cpp-python](https://github.com/abetlen/llama-cpp-python), a Python library with GPU accel, LangChain support, and OpenAI-compatible API server. |
| * [candle](https://github.com/huggingface/candle), a Rust ML framework with a focus on performance, including GPU support, and ease of use. |
| * [ctransformers](https://github.com/marella/ctransformers), a Python library with GPU accel, LangChain support, and OpenAI-compatible AI server. Note, as of time of writing (November 27th 2023), ctransformers has not been updated in a long time and does not support many recent models. |
|
|
| <!-- README_GGUF.md-about-gguf end --> |
| |
| ================================ |
| # #--# Original Model Card #--# |
| ================================ |
| |
| <div align="center"> |
| <img src="https://github.com/InternLM/lmdeploy/assets/36994684/0cf8d00f-e86b-40ba-9b54-dc8f1bc6c8d8" width="600"/> |
| |
| |
| [](https://github.com/InternLM/xtuner) |
| |
| |
| </div> |
| |
| ## Model |
| |
| llava-llama-3-8b-v1_1 is a LLaVA model fine-tuned from [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) and [CLIP-ViT-Large-patch14-336](https://huggingface.co/openai/clip-vit-large-patch14-336) with [ShareGPT4V-PT](https://huggingface.co/datasets/Lin-Chen/ShareGPT4V) and [InternVL-SFT](https://github.com/OpenGVLab/InternVL/tree/main/internvl_chat#prepare-training-datasets) by [XTuner](https://github.com/InternLM/xtuner). |
|
|
| **Note: This model is in GGUF format.** |
|
|
| Resources: |
|
|
| - GitHub: [xtuner](https://github.com/InternLM/xtuner) |
| - HuggingFace LLaVA format model: [xtuner/llava-llama-3-8b-v1_1-transformers](https://huggingface.co/xtuner/llava-llama-3-8b-v1_1-transformers) |
| - Official LLaVA format model: [xtuner/llava-llama-3-8b-v1_1-hf](https://huggingface.co/xtuner/llava-llama-3-8b-v1_1-hf) |
| - XTuner LLaVA format model: [xtuner/llava-llama-3-8b-v1_1](https://huggingface.co/xtuner/llava-llama-3-8b-v1_1) |
|
|
|
|
| ## Details |
|
|
| | Model | Visual Encoder | Projector | Resolution | Pretraining Strategy | Fine-tuning Strategy | Pretrain Dataset | Fine-tune Dataset | |
| | :-------------------- | ------------------: | --------: | ---------: | ---------------------: | ------------------------: | ------------------------: | -----------------------: | |
| | LLaVA-v1.5-7B | CLIP-L | MLP | 336 | Frozen LLM, Frozen ViT | Full LLM, Frozen ViT | LLaVA-PT (558K) | LLaVA-Mix (665K) | |
| | LLaVA-Llama-3-8B | CLIP-L | MLP | 336 | Frozen LLM, Frozen ViT | Full LLM, LoRA ViT | LLaVA-PT (558K) | LLaVA-Mix (665K) | |
| | LLaVA-Llama-3-8B-v1.1 | CLIP-L | MLP | 336 | Frozen LLM, Frozen ViT | Full LLM, LoRA ViT | ShareGPT4V-PT (1246K) | InternVL-SFT (1268K) | |
|
|
| ## Results |
|
|
| <div align="center"> |
| <img src="https://github.com/InternLM/xtuner/assets/36994684/a157638c-3500-44ed-bfab-d8d8249f91bb" alt="Image" width=500" /> |
| </div> |
|
|
| | Model | MMBench Test (EN) | MMBench Test (CN) | CCBench Dev | MMMU Val | SEED-IMG | AI2D Test | ScienceQA Test | HallusionBench aAcc | POPE | GQA | TextVQA | MME | MMStar | |
| | :-------------------- | :---------------: | :---------------: | :---------: | :-------: | :------: | :-------: | :------------: | :-----------------: | :--: | :--: | :-----: | :------: | :----: | |
| | LLaVA-v1.5-7B | 66.5 | 59.0 | 27.5 | 35.3 | 60.5 | 54.8 | 70.4 | 44.9 | 85.9 | 62.0 | 58.2 | 1511/348 | 30.3 | |
| | LLaVA-Llama-3-8B | 68.9 | 61.6 | 30.4 | 36.8 | 69.8 | 60.9 | 73.3 | 47.3 | 87.2 | 63.5 | 58.0 | 1506/295 | 38.2 | |
| | LLaVA-Llama-3-8B-v1.1 | 72.3 | 66.4 | 31.6 | 36.8 | 70.1 | 70.0 | 72.9 | 47.7 | 86.4 | 62.6 | 59.0 | 1469/349 | 45.1 | |
|
|
|
|
| ## Quickstart |
|
|
| ### Download models |
|
|
| ```bash |
| # mmproj |
| wget https://huggingface.co/xtuner/llava-llama-3-8b-v1_1-gguf/resolve/main/llava-llama-3-8b-v1_1-mmproj-f16.gguf |
| |
| # fp16 llm |
| wget https://huggingface.co/xtuner/llava-llama-3-8b-v1_1-gguf/resolve/main/llava-llama-3-8b-v1_1-f16.gguf |
| |
| # int4 llm |
| wget https://huggingface.co/xtuner/llava-llama-3-8b-v1_1-gguf/resolve/main/llava-llama-3-8b-v1_1-int4.gguf |
| |
| # (optional) ollama fp16 modelfile |
| wget https://huggingface.co/xtuner/llava-llama-3-8b-v1_1-gguf/resolve/main/OLLAMA_MODELFILE_F16 |
| |
| # (optional) ollama int4 modelfile |
| wget https://huggingface.co/xtuner/llava-llama-3-8b-v1_1-gguf/resolve/main/OLLAMA_MODELFILE_INT4 |
| ``` |
|
|
| ### Chat by `ollama` |
|
|
| ```bash |
| # fp16 |
| ollama create llava-llama3-f16 -f ./OLLAMA_MODELFILE_F16 |
| ollama run llava-llama3-f16 "xx.png Describe this image" |
| |
| # int4 |
| ollama create llava-llama3-int4 -f ./OLLAMA_MODELFILE_INT4 |
| ollama run llava-llama3-int4 "xx.png Describe this image" |
| ``` |
|
|
| ### Chat by `llama.cpp` |
|
|
| 1. Build [llama.cpp](https://github.com/ggerganov/llama.cpp) ([docs](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage)) . |
| 2. Build `./llava-cli` ([docs](https://github.com/ggerganov/llama.cpp/tree/master/examples/llava#usage)). |
|
|
| Note: llava-llama-3-8b-v1_1 uses the Llama-3-instruct chat template. |
| |
| ```bash |
| # fp16 |
| ./llava-cli -m ./llava-llama-3-8b-v1_1-f16.gguf --mmproj ./llava-llama-3-8b-v1_1-mmproj-f16.gguf --image YOUR_IMAGE.jpg -c 4096 -e -p "<|start_header_id|>user<|end_header_id|>\n\n<image>\nDescribe this image<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n" |
| |
| # int4 |
| ./llava-cli -m ./llava-llama-3-8b-v1_1-int4.gguf --mmproj ./llava-llama-3-8b-v1_1-mmproj-f16.gguf --image YOUR_IMAGE.jpg -c 4096 -e -p "<|start_header_id|>user<|end_header_id|>\n\n<image>\nDescribe this image<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n" |
| ``` |
| |
| ### Reproduce |
| |
| Please refer to [docs](https://github.com/InternLM/xtuner/tree/main/xtuner/configs/llava/llama3_8b_instruct_clip_vit_large_p14_336#readme). |
| |
| ## Citation |
| |
| ```bibtex |
| @misc{2023xtuner, |
| title={XTuner: A Toolkit for Efficiently Fine-tuning LLM}, |
| author={XTuner Contributors}, |
| howpublished = {\url{https://github.com/InternLM/xtuner}}, |
| year={2023} |
| } |
| ``` |
