datablations
gptqlora
| datablations | gptqlora | |
|---|---|---|
| 6 | 2 | |
| 290 | 94 | |
| 3.8% | - | |
| 6.9 | 7.6 | |
| about 1 month ago | 11 months ago | |
| Jupyter Notebook | Python | |
| Apache License 2.0 | MIT License |
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datablations
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Gemini is only 1x Chinchilla, so it undertrained for production
1x chinchilla means it's not really undertrained but that more could be squeezed without excessive difficulty https://arxiv.org/abs/2305.16264
- Can LLMs learn from a single example?
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Chinchilla’s Death
You might want to give a read to "Scaling Data-Constrained Language Models" [1]. They basically generalized the Chinchilla scaling law by investigating behavior on multi-epoch runs.
[1] https://arxiv.org/abs/2305.16264
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RWKV Pile+ seems to be training on far more tokens than any LLM ever has
I would imagine that there is a lot of overlap, yeah. That said, training on repeated data does seem to be effective at this level.
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(2/2) May 2023
Scaling Data-Constrained Language Models (https://arxiv.org/abs/2305.16264)
- How to Keep Scaling Large Language Models when Data Runs Out? A New AI Research Trains 400 Models with up to 9B Parameters and 900B Tokens to Create an Extension of Chinchilla Scaling Laws for Repeated Data
gptqlora
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(2/2) May 2023
GPTQLoRA: Efficient Finetuning of Quantized LLMs with GPTQ (https://github.com/qwopqwop200/gptqlora/tree/main)
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GPTQLoRA: Efficient Finetuning of Quantized LLMs with GPTQ
The difference from QLoRA is that GPTQ is used instead of NF4 (Normal Float4) + DQ (Double Quantization) for model quantization. The advantage is that you can expect better performance because it provides better quantization than conventional bitsandbytes. The downside is that it is a one-shot quantization methodology, so it is more inconvenient than bitsandbytes, and unlike bitsandbytes, it is not universal. I'm still experimenting, but it seems to work. At least, I hope it can be more options for people using LoRA. https://github.com/qwopqwop200/gptqlora/tree/main
What are some alternatives?
TinyLlama - The TinyLlama project is an open endeavor to pretrain a 1.1B Llama model on 3 trillion tokens.
tree-of-thoughts - Plug in and Play Implementation of Tree of Thoughts: Deliberate Problem Solving with Large Language Models that Elevates Model Reasoning by atleast 70%
airoboros - Customizable implementation of the self-instruct paper.
GirlfriendGPT - Girlfriend GPT is a Python project to build your own AI girlfriend using ChatGPT4.0
chathub - All-in-one chatbot client
prompt-engineering - Tips and tricks for working with Large Language Models like OpenAI's GPT-4.
chain-of-thought-hub - Benchmarking large language models' complex reasoning ability with chain-of-thought prompting
SuperAGI - <⚡️> SuperAGI - A dev-first open source autonomous AI agent framework. Enabling developers to build, manage & run useful autonomous agents quickly and reliably.
guidance - A guidance language for controlling large language models. [Moved to: https://github.com/guidance-ai/guidance]
gorilla - Gorilla: An API store for LLMs