llava
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[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
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Aug 12, 2024 - Python
SGLang is a fast serving framework for large language models and vision language models.
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Jan 18, 2025 - Python
SUPIR aims at developing Practical Algorithms for Photo-Realistic Image Restoration In the Wild. Our new online demo is also released at suppixel.ai.
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Jul 30, 2024 - Python
An efficient, flexible and full-featured toolkit for fine-tuning LLM (InternLM2, Llama3, Phi3, Qwen, Mistral, ...)
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Jan 14, 2025 - Python
Data processing for and with foundation models! 🍎 🍋 🌽 ➡️ ➡️🍸 🍹 🍷
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Jan 17, 2025 - Python
中文nlp解决方案(大模型、数据、模型、训练、推理)
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Jan 2, 2025 - Jupyter Notebook
Open-source evaluation toolkit of large vision-language models (LVLMs), support 160+ VLMs, 50+ benchmarks
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Jan 16, 2025 - Python
[ACL 2024 🔥] Video-ChatGPT is a video conversation model capable of generating meaningful conversation about videos. It combines the capabilities of LLMs with a pretrained visual encoder adapted for spatiotemporal video representation. We also introduce a rigorous 'Quantitative Evaluation Benchmarking' for video-based conversational models.
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Aug 27, 2024 - Python
Build multimodal language agents for very fast prototype and production
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Jan 17, 2025 - Python
Pocket-Sized Multimodal AI for content understanding and generation across multilingual texts, images, and 🔜 video, up to 5x faster than OpenAI CLIP and LLaVA 🖼️ & 🖋️
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Jan 3, 2025 - Python
Tag manager and captioner for image datasets
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Dec 13, 2024 - Python
🔥🔥 LLaVA++: Extending LLaVA with Phi-3 and LLaMA-3 (LLaVA LLaMA-3, LLaVA Phi-3)
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Jul 10, 2024 - Python
A Framework of Small-scale Large Multimodal Models
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Dec 18, 2024 - Python
MLX-VLM is a package for inference and fine-tuning of Vision Language Models (VLMs) on your Mac using MLX.
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Jan 17, 2025 - Python
👁️ + 💬 + 🎧 = 🤖 Curated list of top foundation and multimodal models! [Paper + Code + Examples + Tutorials]
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Feb 29, 2024 - Python
Famous Vision Language Models and Their Architectures
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Sep 8, 2024 - Markdown
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