Model
llava-phi-3-mini is a LLaVA model fine-tuned from microsoft/Phi-3-mini-4k-instruct and CLIP-ViT-Large-patch14-336 with ShareGPT4V-PT and InternVL-SFT by XTuner.
Note: This model is in GGUF format.
Resources:
- GitHub: xtuner
- Official LLaVA format model: xtuner/llava-phi-3-mini
- HuggingFace LLaVA format model: xtuner/llava-phi-3-mini-hf
- XTuner LLaVA format model: xtuner/llava-phi-3-mini-xtuner
Details
| Model | Visual Encoder | Projector | Resolution | Pretraining Strategy | Fine-tuning Strategy | Pretrain Dataset | Fine-tune Dataset | Pretrain Epoch | Fine-tune Epoch |
|---|---|---|---|---|---|---|---|---|---|
| LLaVA-v1.5-7B | CLIP-L | MLP | 336 | Frozen LLM, Frozen ViT | Full LLM, Frozen ViT | LLaVA-PT (558K) | LLaVA-Mix (665K) | 1 | 1 |
| LLaVA-Llama-3-8B | CLIP-L | MLP | 336 | Frozen LLM, Frozen ViT | Full LLM, LoRA ViT | LLaVA-PT (558K) | LLaVA-Mix (665K) | 1 | 1 |
| LLaVA-Llama-3-8B-v1.1 | CLIP-L | MLP | 336 | Frozen LLM, Frozen ViT | Full LLM, LoRA ViT | ShareGPT4V-PT (1246K) | InternVL-SFT (1268K) | 1 | 1 |
| LLaVA-Phi-3-mini | CLIP-L | MLP | 336 | Frozen LLM, Frozen ViT | Full LLM, Full ViT | ShareGPT4V-PT (1246K) | InternVL-SFT (1268K) | 1 | 2 |
Results
| Model | MMBench Test (EN) | MMMU Val | SEED-IMG | AI2D Test | ScienceQA Test | HallusionBench aAcc | POPE | GQA | TextVQA | MME | MMStar |
|---|---|---|---|---|---|---|---|---|---|---|---|
| LLaVA-v1.5-7B | 66.5 | 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 | 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 | 37.1 | 70.1 | 70.0 | 72.9 | 47.7 | 86.4 | 62.6 | 59.0 | 1469/349 | 45.1 |
| LLaVA-Phi-3-mini | 69.2 | 41.4 | 70.0 | 69.3 | 73.7 | 49.8 | 87.3 | 61.5 | 57.8 | 1477/313 | 43.7 |
Quickstart
Download models
# mmproj
wget https://huggingface.co/xtuner/llava-phi-3-mini-gguf/resolve/main/llava-phi-3-mini-mmproj-f16.gguf
# fp16 llm
wget https://huggingface.co/xtuner/llava-phi-3-mini-gguf/resolve/main/llava-phi-3-mini-f16.gguf
# int4 llm
wget https://huggingface.co/xtuner/llava-phi-3-mini-gguf/resolve/main/llava-phi-3-mini-int4.gguf
# (optional) ollama fp16 modelfile
wget https://huggingface.co/xtuner/llava-phi-3-mini-gguf/resolve/main/OLLAMA_MODELFILE_F16
# (optional) ollama int4 modelfile
wget https://huggingface.co/xtuner/llava-phi-3-mini-gguf/resolve/main/OLLAMA_MODELFILE_INT4
Chat by ollama
Note: llava-phi-3-mini uses the Phi-3-instruct chat template.
# fp16
ollama create llava-phi3-f16 -f ./OLLAMA_MODELFILE_F16
ollama run llava-phi3-f16 "xx.png Describe this image"
# int4
ollama create llava-phi3-int4 -f ./OLLAMA_MODELFILE_INT4
ollama run llava-phi3-int4 "xx.png Describe this image"
Chat by ./llava-cli
Note: llava-phi-3-mini uses the Phi-3-instruct chat template.
# fp16
./llava-cli -m ./llava-phi-3-mini-f16.gguf --mmproj ./llava-phi-3-mini-mmproj-f16.gguf --image YOUR_IMAGE.jpg -c 4096
# int4
./llava-cli -m ./llava-phi-3-mini-int4.gguf --mmproj ./llava-phi-3-mini-mmproj-f16.gguf --image YOUR_IMAGE.jpg -c 4096
Reproduce
Please refer to docs.
Citation
@misc{2023xtuner,
title={XTuner: A Toolkit for Efficiently Fine-tuning LLM},
author={XTuner Contributors},
howpublished = {\url{https://github.com/InternLM/xtuner}},
year={2023}
}