haotian-liu/LLaVA
[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
Loading star history...
Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
The project lists 47 contributors on GitHub.
Gained 48% fewer stars in the last 90 days than in the 90 days before.
Use Cases & Benefits
- Implements visual instruction tuning to build large multimodal language and vision models with GPT-4V level capabilities.
- Enables efficient training and inference of multimodal models with support for low-bit quantization and multi-GPU setups, reducing resource requirements.
- Use for developing advanced chatbots that understand and respond to both text and images in a conversational manner.
- Use for research and development of multimodal AI assistants capable of complex visual question answering and instruction following.
- Use for deploying scalable multimodal AI services with flexible model serving via Gradio UI, CLI, or SGLang workers on diverse hardware.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Apache 2.0
Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.
Community files
- README: present
Watch-outs
- Warning: No commits in over a year (last push Aug 2024).
General guidance from repository metadata, not legal advice. How we score
From the README
Visual instruction tuning towards large language and vision models with GPT-4 level capabilities.
Improved Baselines with Visual Instruction Tuning [Paper] [HF]
Visual Instruction Tuning (NeurIPS 2023, Oral) [Paper] [HF]
Usage and License Notices: This project utilizes certain datasets and checkpoints that are subject to their respective original licenses. Users must comply with all terms and conditions of these original licenses, including but not limited to the OpenAI Terms of Use for the dataset and the specific licenses for base language models for checkpoints trained using the dataset (e.g. Llama community license for LLaMA-2 and Vicuna-v1.5). This project does not impose any additional constraints beyond those stipulated in the original licenses. Furthermore, users are reminded to ensure that their use of the dataset and checkpoints is in compliance with all applicable laws and regulations.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
Forks
2.8K-6
Open issues
1.1K-1
Compared with peers in AI
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 8, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| D4Vinci/Scrapling | 101.1K | +6.3K | 75 | 6 days ago |
| thedotmack/claude-mem | 115.8K | +4.7K | 75 | today |
| heygen-com/hyperframes | 82.3K | +4.0K | 75 | today |
| harry0703/MoneyPrinterTurbo | 142.0K | +3.8K | 75 | 3 days ago |
| github/spec-kit | 149.2K | +2.6K | 75 | today |
| haotian-liu/LLaVA | 25.1K | — | 33 | — |
| Category median | 115.8K | +4.0K | 75 | — |
Discover Repositories
Search across tracked repositories by name or description