NExT-GPT
visual-med-alpaca
| NExT-GPT | visual-med-alpaca | |
|---|---|---|
| 1 | 2 | |
| 2,882 | 341 | |
| - | 2.3% | |
| 9.3 | 6.0 | |
| 4 months ago | 2 months ago | |
| Python | Python | |
| BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
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NExT-GPT
visual-med-alpaca
- Local medical LLM
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Open-source LLMs cherry-picking? [D]
Medical: I thought it was OpenAI that banned their model for medical uses, turns out that's LLaMA and all subsequent models, including the visual-med-alpaca I was going to hold up as an example of small models doing well. (For their cherry-picked examples, it's still not far off, which is quite good for 7B params. See here.)
What are some alternatives?
mPLUG-Owl - mPLUG-Owl & mPLUG-Owl2: Modularized Multimodal Large Language Model
InternChat - InternGPT / InternChat allows you to interact with ChatGPT by clicking, dragging and drawing using a pointing device. [Moved to: https://github.com/OpenGVLab/InternGPT]
gpt_academic - 为GPT/GLM等LLM大语言模型提供实用化交互接口，特别优化论文阅读/润色/写作体验，模块化设计，支持自定义快捷按钮&函数插件，支持Python和C++等项目剖析&自译解功能，PDF/LaTex论文翻译&总结功能，支持并行问询多种LLM模型，支持chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, moss等。
Huatuo-Llama-Med-Chinese - Repo for BenTsao [original name: HuaTuo (华驼)], Instruction-tuning Large Language Models with Chinese Medical Knowledge. 本草（原名：华驼）模型仓库，基于中文医学知识的大语言模型指令微调
DoctorGLM - 基于ChatGLM-6B的中文问诊模型
Video-LLaMA - [EMNLP 2023 Demo] Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding
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.
InternGPT - InternGPT (iGPT) is an open source demo platform where you can easily showcase your AI models. Now it supports DragGAN, ChatGPT, ImageBind, multimodal chat like GPT-4, SAM, interactive image editing, etc. Try it at igpt.opengvlab.com (支持DragGAN、ChatGPT、ImageBind、SAM的在线Demo系统)
unilm - Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities