Model details
Model type: LLaVA is an open-source chatbot trained by fine-tuning LLaMA/Vicuna on GPT-generated multimodal instruction-following data. It is an auto-regressive language model, based on the transformer architecture.

Model date: LLaVA-flint-v0.5-1B was trained in Nov 2023.


This model is an implementation of Llava using the TinyLlama 1.1b as the frozen llm model

It's designed to be able to run in low-resource environments
We plan to release further versions designed for specific tasks so stay tuned.


Paper or resources for more information on the original Llava: https://llava-vl.github.io/

License
Apache 2 (TinyLlama)
Where to send questions or comments about the model: ask me here on huggingface :)

Intended use
Primary intended uses: The primary use of LLaVA is research on large multimodal models and chatbots.

Primary intended users: The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence.

Training dataset
558K filtered image-text pairs from LAION/CC/SBU, captioned by BLIP.
158K GPT-generated multimodal instruction-following data.
450K academic-task-oriented VQA data mixture.
40K ShareGPT data.
Evaluation dataset
A collection of 12 benchmarks, including 5 academic VQA benchmarks and 7 recent benchmarks specifically proposed for instruction-following LMMs.




{"license": "mit"}
transformers pytorch llava text-generation license:mit autotrain_compatible endpoints_compatible region:us