Video-LLaMA
Chinese-LLaMA-Alpaca
| Video-LLaMA | Chinese-LLaMA-Alpaca | |
|---|---|---|
| 8 | 4 | |
| 2,455 | 17,539 | |
| 5.8% | - | |
| 6.6 | 8.3 | |
| 5 days ago | 16 days ago | |
| Python | Python | |
| BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
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Video-LLaMA
- Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding
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OpenAI vs Google, Detect ChatGPT Content with 99% accuracy, Navigating AI compute costs
👀 Video-LLaMA - Empower large language models with video and audio understanding capability. (link) 🦦 Otter - Multi-modal model with improved instruction-following and in-context learning ability. 🔗 Linkly.AI - AI-powered lead analytics and management platform that helps you track, analyze, and streamline your leads in one place. 🎬 Jet Cut Ready - AI plugin for Adobe Premiere Pro that automatically removes silent parts in videos. (link) 💬 HeyGen's ChatGPT Plugin - Convert text into high-quality videos using AI text and video generation.
- Video-LLaMA: Instruction-Tuned Audio-Visual Lang Model for Video Understanding
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Unleash the Power of Video-LLaMA: Revolutionizing Language Models with Video and Audio Understanding!
Prepare to be blown away by the cutting-edge Video-LLaMA project! We're pushing the boundaries of language models by equipping them with the remarkable ability to comprehend video and audio. Get ready for an extraordinary adventure! 🌟
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Video-LLaMA An Instruction-tuned Audio-Visual Language Model for Video Understanding
Source Code: The codebase for pre-training and fine-tuning the Video-LLaMA model as well as the model weights are available on GitHub: https://github.com/DAMO-NLP-SG/Video-LLaMA
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Video-ChatGPT: Redefining Interactions with Visual Data
Tons of cool stuff happening in the space, also recently saw the LLaMa-Video version of this - https://github.com/DAMO-NLP-SG/Video-LLaMA
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Meet Video-LLaMA: A Multi-Modal Framework that Empowers Large Language Models (LLMs) with the Capability of Understanding both Visual and Auditory Content in the Video
Code: https://github.com/DAMO-NLP-SG/Video-LLaMA
Chinese-LLaMA-Alpaca
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Chinese-Alpaca-Plus-13B-GPTQ
I'd like to share with you today the Chinese-Alpaca-Plus-13B-GPTQ model, which is the GPTQ format quantised 4bit models of Yiming Cui's Chinese-LLaMA-Alpaca 13B for GPU reference.
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How to train a new language that is not in base model?
Could follow what people did with the Chinese-LLaMA, just for Korean. Might want to have a pure Korean corpus before feeding in a translation dataset. How big is it by the way?
- Open Source Chinese LLMs
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Its possible to fine tune the llama model to better understand another language?
Chinese: https://github.com/ymcui/Chinese-LLaMA-Alpaca
What are some alternatives?
mPLUG-Owl - mPLUG-Owl & mPLUG-Owl2: Modularized Multimodal Large Language Model
ChatGLM2-6B - ChatGLM2-6B: An Open Bilingual Chat LLM | 开源双语对话语言模型
NExT-GPT - Code and models for NExT-GPT: Any-to-Any Multimodal Large Language Model
CodeCapybara - Open-source Self-Instruction Tuning Code LLM
Otter - 🦦 Otter, a multi-modal model based on OpenFlamingo (open-sourced version of DeepMind's Flamingo), trained on MIMIC-IT and showcasing improved instruction-following and in-context learning ability.
LLMSurvey - The official GitHub page for the survey paper "A Survey of Large Language Models".
LLaVA - [NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
paxml - Pax is a Jax-based machine learning framework for training large scale models. Pax allows for advanced and fully configurable experimentation and parallelization, and has demonstrated industry leading model flop utilization rates.
MiniGPT-4-discord-bot - A true multimodal LLaMA derivative -- on Discord!
Qwen-VL - The official repo of Qwen-VL (通义千问-VL) chat & pretrained large vision language model proposed by Alibaba Cloud.
LLM-Agent-Paper-List - The paper list of the 86-page paper "The Rise and Potential of Large Language Model Based Agents: A Survey" by Zhiheng Xi et al.
Cornucopia-LLaMA-Fin-Chinese - 聚宝盆(Cornucopia): 中文金融系列开源可商用大模型，并提供一套高效轻量化的垂直领域LLM训练框架(Pretraining、SFT、RLHF、Quantize等)