visual-chatgpt
| minimal-llama | visual-chatgpt | |
|---|---|---|
| 4 | 50 | |
| 456 | 31,684 | |
| - | - | |
| 8.5 | 8.9 | |
| 7 months ago | about 1 year ago | |
| Python | Python | |
| - | MIT License |
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minimal-llama
- Show HN: Finetune LLaMA-7B on commodity GPUs using your own text
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Visual ChatGPT
I can't edit my comment now, but it's 30B that needs 18GB of VRAM.
LLaMA-13B, GPT-3 175B level, only needs 10GB of VRAM with the GPTQ 4bit quantization.
>do you think there's anything left to trim? like weight pruning, or LoRA, or I dunno, some kind of Huffman coding scheme that lets you mix 4-bit, 2-bit and 1-bit quantizations?
Absolutely. The GPTQ paper claims negligible output quality loss with 3-bit quantization. The GPTQ-for-LLaMA repo supports 3-bit quantization and inference. So this extra 25% savings is already possible.
As of right GPTQ-for-LLaMA is using a VRAM hungry attention method. Flash attention will reduce the requirements for 7B to 4GB and possibly fit 30B with a 2048 context window into 16GB, all before stacking 3-bit.
Pruning is a possibility but I'm not aware of anyone working on it yet.
LoRa has already been implemented. See https://github.com/zphang/minimal-llama#peft-fine-tuning-wit...
visual-chatgpt
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Subtler Flex
For prompting, the GitHub repo I refer to the most is actually one from Microsoft: https://github.com/Microsoft/Visual-ChatGPT
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OpenDILab Awesome Paper Collection: RL with Human Feedback （1）
Found relevant code at https://github.com/microsoft/visual-chatgpt + all code implementations here
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[R] Low-code LLM: Visual Programming over LLMs - Yuzhe Cai et al , Microsoft Research Asia 2023
Github: https://github.com/microsoft/visual-chatgpt/tree/main/LowCodeLLM will soon be available!
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It's been a week and there's already front ends for auto GPT. Is anyone else having a hard time keeping up with the take off? Are we seeing what exponential looks like?
It's not so much the size of the LLMs, it's what people are able to do with them in novel ways, e.g. https://github.com/microsoft/visual-chatgpt/tree/main/TaskMatrix.AI
- Taskmatrix.ai
- Introducing JARVIS : the new Microsoft's autonomous AI powered by HuggingGPT and ChatGPT.
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How to make ChatGPT run tasks
There is a python library langchain, which microsoft used to give it access to image editing tools. You can write your own tools for it very easily, I've been having fun with it. I gave it internet search tools and it worked great at using current events in the response.
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An AI researcher who has been warning about the technology for over 20 years says we should 'shut it all down,' and issue an 'indefinite and worldwide' ban.
Something like this: https://github.com/microsoft/visual-chatgpt/tree/main/TaskMatrix.AI could enable a far simpler AI to start making copies of itself.
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HuggingGPT: Solving AI Tasks with ChatGPT and Its Friends in HuggingFace
Reminds me of VisualChatGPT (https://github.com/microsoft/visual-chatgpt), which also uses a LLM to decide what vision models to run.
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ChatGPT is Inform8: interactive fiction with dual narration and action planes (both playable), dialogues, inner thoughts and the ability to argue about narration to change the course of action.
The best Microsoft API or overall API? It really depends what your goal is. https://github.com/huggingface is great if you want to dive right in, but https://github.com/microsoft/visual-chatgpt might be good as well (not easy to get to work locally).
What are some alternatives?
FlexGen - Running large language models on a single GPU for throughput-oriented scenarios.
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
whisper.cpp - Port of OpenAI's Whisper model in C/C++
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
simple-llm-finetuner - Simple UI for LLM Model Finetuning
roomGPT - Upload a photo of your room to generate your dream room with AI.
alpaca-lora - Instruct-tune LLaMA on consumer hardware
JARVIS - JARVIS, a system to connect LLMs with ML community. Paper: https://arxiv.org/pdf/2303.17580.pdf
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ
ControlNet - Let us control diffusion models!
pybroker - Algorithmic Trading in Python with Machine Learning