recurrent-memory-transformer-pytorch
PaLM-rlhf-pytorch
| recurrent-memory-transformer-pytorch | PaLM-rlhf-pytorch | |
|---|---|---|
| 1 | 25 | |
| 381 | 7,598 | |
| - | - | |
| 7.4 | 4.6 | |
| 3 months ago | 4 months ago | |
| Python | Python | |
| MIT License | MIT License |
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recurrent-memory-transformer-pytorch
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The race is on
Of course, lucidrains already has an empty repo up. So that's worth keeping an eye on.
PaLM-rlhf-pytorch
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How should I get an in-depth mathematical understanding of generative AI?
ChatGPT isn't open sourced so we don't know what the actual implementation is. I think you can read Open Assistant's source code for application design. If that is too much, try Open Chat Toolkit's source code for developer tools . If you need very bare implementation, you should go for lucidrains/PaLM-rlhf-pytorch.
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[P] Open-source PaLM models trained at 8k context length
AFAIK, it is not. They are using the open-source re-implementation of Phil Wang (aka lucidrains), which is available here: https://github.com/lucidrains/PaLM-rlhf-pytorch
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Should AI language models be free software?
Not sure what do you mean by putting source code in double quote, but I don't think the source code is petabytes of text. GPT-2 implementation is few hundred lines of Python (in HuggingFace). PaLM + RLHF - Pytorch (Basically ChatGPT but with PaLM) is less than 1000 lines.
- Would a decentralized open-source platform of ChatGPT work?
- Exciting new shit.
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Top 10 Best Open Source GitHub repos for Developers 2023
GitHub Link: https://github.com/lucidrains/PaLM-rlhf-pytorch
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Gather up great coders and make a better Character.Ai
Well... Not necessarily. Actually, if you want to be extra thrifty, you could even go without an ML expert. Just use an open-source one, like LaMDA or PaLM. After that, use chatGPT to build you a basic front end (which would still be better than CAI lol).
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Open-Source competitor to OpenAI?
and PaLM with RLHF from Phil Wang (open model, needs to be trained): https://github.com/lucidrains/PaLM-rlhf-pytorch
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Microsoft in talks to acquire a 49% stake in ChatGPT owner OpenAI
Closest you can get is probably with Google T5-Flan [1].
It is not the size of the model or the text it was trained on that makes ChatGPT so performant. It is the additional human assisted training to make it respond well to instructions. Open source versions of that are just starting to see the light of day [2].
[1] https://huggingface.co/google/flan-t5-xxl
[2] https://github.com/lucidrains/PaLM-rlhf-pytorch
- Will we have a free version of ChatGPT (GPT-3) similar to Stable Diffusion?
What are some alternatives?
musiclm-pytorch - Implementation of MusicLM, Google's new SOTA model for music generation using attention networks, in Pytorch
nanoGPT - The simplest, fastest repository for training/finetuning medium-sized GPTs.
muse-maskgit-pytorch - Implementation of Muse: Text-to-Image Generation via Masked Generative Transformers, in Pytorch
GLM-130B - GLM-130B: An Open Bilingual Pre-Trained Model (ICLR 2023)
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
ggml - Tensor library for machine learning
trlx - A repo for distributed training of language models with Reinforcement Learning via Human Feedback (RLHF)
Open-Assistant - OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.
Rath - Next generation of automated data exploratory analysis and visualization platform.
FlexGen - Running large language models like OPT-175B/GPT-3 on a single GPU. Focusing on high-throughput generation. [Moved to: https://github.com/FMInference/FlexGen]
petals - 🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
ColossalAI - Making large AI models cheaper, faster and more accessible