ChatGLM-6B
self-instruct
| ChatGLM-6B | self-instruct | |
|---|---|---|
| 17 | 3 | |
| 39,341 | 3,666 | |
| 1.6% | - | |
| 8.4 | 2.3 | |
| 3 months ago | about 1 year ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
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ChatGLM-6B
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What are the current fastest multi-gpu inference frameworks?
ChatGLM seems to be pretty popular but I've never used this before.
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A CEO is spending more than $2,000 a month on ChatGPT Plus accounts for all of his employees, and he says it's saving 'hours' of time
There are also locally hosted options that approach the effectiveness of ChatGPT. This GLM for example was specifically trained to be able to be processed on a single consumer grade GPU
- Open Source Chinese LLMs
- ChatGLM-6B: run locally on consumer graphics card (6GB of GPU memory required)
- Ask HN: Open source LLM for commercial use?
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Coding LLaMa Modell?
A link to for y'all. Definitely gonna try to mess around with this!
- 关于GPT，AI和未来的一些社会经济问题，向诸位请教
- FLiPN-FLaNK Stack Weekly for 20 March 2023
- ChatGLM-6B - an open source 6.2 billion parameter English/Chinese bilingual LLM trained on 1T tokens, supplemented by supervised fine-tuning, feedback bootstrap, and Reinforcement Learning from Human Feedback. Runs on consumer grade GPUs
- ChatGLM: Open bilingual language model based on General Language Model framework
self-instruct
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The next generation of AI for developers and Google Workspace
When they say Augment your dataset with synthetic data on https://developers.googleblog.com/2023/03/announcing-palm-ap... do they mean something like this https://github.com/yizhongw/self-instruct ?
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Alpaca- An Instruct Tuned Llama 7B. Responses on par with txt-DaVinci-3. Demo up
It says
> We train the Alpaca model on 52K instruction-following demonstrations generated in the style of self-instruct using text-davinci-003
Which leads to self-instruct https://github.com/yizhongw/self-instruct
From a glimpse they used a LM to classify instructions & train the model which IMHO very similar to RLHF
- Alpaca: A Strong Open-Source Instruction-Following Model
What are some alternatives?
llama.cpp - LLM inference in C/C++
CodeCapypara - [Moved to: https://github.com/FSoft-AI4Code/CodeCapybara]
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM
stanford_alpaca - Code and documentation to train Stanford's Alpaca models, and generate the data.
LongForm - Reverse Instructions to generate instruction tuning data with corpus examples
Open-Assistant - OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.
datagen - Generate authentic looking mock data based on a SQL, JSON or Avro schema and produce to Kafka in JSON or Avro format.
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
basaran - Basaran is an open-source alternative to the OpenAI text completion API. It provides a compatible streaming API for your Hugging Face Transformers-based text generation models.
replika-research - Replika.ai Research Papers, Posters, Slides & Datasets