GLM-130B
Open-Assistant
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| GLM-130B | Open-Assistant | |
|---|---|---|
| 19 | 329 | |
| 7,607 | 36,622 | |
| 0.9% | 0.7% | |
| 4.8 | 9.1 | |
| 9 months ago | about 1 month ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
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GLM-130B
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GLM-130B
The https://github.com/THUDM/GLM-130B model is trained on The Pile and can run on 4x3090 when quantized to INT4. I'm wondering if anyone knows if this model could (or has) been quantized using GPTQ, which gives some impressive performance gains over traditional quantization, and I'm also wondering if anyone has tried a 3-bit or 2-bit quantization of such a massive model (using GPTQ). Are there any inherent limitations in this? Is there anything about this model that prevents it from being run on text-generation-webui?
- Has anyone tried GLM?
- Ask HN: Open source LLM for commercial use?
- Whichever way I look at it, I just don’t see this being the case. Why do you agree/disagree?
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The New Bing and ChatGPT
> GLM-130B, a model comparable with GPT-3, has 130 billion parameters in FP16 precision, a total of 260G of GPU memory is required to store model weights. The DGX-A100 server has 8 A100s and provides an amount of 320G of GPU memory (640G for 80G A100 version) so it suits GLM-130B well.
https://github.com/THUDM/GLM-130B/blob/main/docs/low-resourc...
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OpenAI Major Outage
GLM-130B[1] (a 130 billion parameter model vs GPT-3's 175 billion parameter model) is able to run optimally on consumer level high-end hardware, 4xRTX 3090 in particular. That's < $4k at current prices, and as hardware prices go one can only imagine what it'll be in a year or two. It also enables running with degraded performance on lesser systems.
It's a whole lot cheaper to run neural net style systems than to train them. "Somebody on Twitter"[2] got it setup, and broke down the costs, demonstrated some prompts, and what not. Cliff notes being a fraction of a penny per query, with each taking about 16s to generate. The output's pretty terrible, but it's unclear to me whether that's inherent or a result of priority. I expect OpenAI spent a lot of manpower on supervised training, whereas this system probably had minimal, especially in English (it's from a Chinese university).
[1] - https://github.com/THUDM/GLM-130B
[2] - https://twitter.com/alexjc/status/1617152800571416577
- [D]Are there any known AI systems today that are significantly more advanced than chatGPT ?
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Will there ever be a "Stable Diffusion chat AI" that we can run at home like one can do with Stable Diffusion? A "roll-your-own at home ChatGPT"?
GLM-130B in 4 bit mode is better than GPT3 and can run on 4 RTX-3090s. Still expensive but it’s getting closer. https://github.com/THUDM/GLM-130B
- Open-Source competitor to OpenAI?
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Ask HN: Can you crowdfund the compute for GPT?
https://github.com/THUDM/GLM-130B might be a useful place to look
Open-Assistant
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Best open source AI chatbot alternative?
For open assistant, the code: https://github.com/LAION-AI/Open-Assistant/tree/main/inference
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GPT-4 Turbo for free with no sign up, and most importantly no Bing
Is this being used to collect chat results for synthetic data and/or training like https://github.com/LAION-AI/Open-Assistant did? I believe they gave away GPT-4 api calls via a text interface and absorbed the cost to later build a dataset of chats.
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OpenAI now sends email threats?!
https://open-assistant.io seems to have the same guardrails, as ChatGPT. Tried it on several prompts and it wouldn't comply.
- ChatGPT-Antworten nach Schulnoten bewerten
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Chat GPT Alternatives?
Open-Assistant [https://open-assistant.io/]
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What are the best AI tools you've ACTUALLY used?
Open Assistant by LAION AI on GitHub
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Keep Artificial Intelligence Free, protect it from monopolies: please sign this petition
To add to this if you want something for free or at least close to free, contribute to OpenSource projects like https://open-assistant.io/
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If I had to get someone from total zero to ChatGPT power user
Also, there are fairly useful alternatives like GPT4ALL and Open Assistant that you can run locally.
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Compiling a Comprehensive List of Publicly Usable LLM Q&A Services - Need Your Input!
https://open-assistant.io - oasst-sft-6-llama-30b
- Proposal for a Crowd-Sourced AI Feedback System
What are some alternatives?
PaLM-rlhf-pytorch - Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM
KoboldAI-Client
ggml - Tensor library for machine learning
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
petals - 🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
llama.cpp - LLM inference in C/C++
lm-human-preferences - Code for the paper Fine-Tuning Language Models from Human Preferences
llama - Inference code for Llama models
hivemind - Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.
gpt4all - gpt4all: run open-source LLMs anywhere
metaseq - Repo for external large-scale work
stanford_alpaca - Code and documentation to train Stanford's Alpaca models, and generate the data.