peft
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning. (by huggingface)
ue5-llama-lora
A proof-of-concept project that showcases the potential for using small, locally trainable LLMs to create next-generation documentation tools. (by bublint)
| peft | ue5-llama-lora | |
|---|---|---|
| 26 | 16 | |
| 13,877 | 450 | |
| 4.1% | - | |
| 9.7 | 2.9 | |
| 4 days ago | about 1 year ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
peft
Posts with mentions or reviews of peft.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-12-05.
- LoftQ: LoRA-fine-tuning-aware Quantization
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Fine Tuning Mistral 7B on Magic the Gathering Draft
There is not a lot of great content out there making this clear, but basically all that matters for basic fine tuning is how much VRAM you have -- since the 3090 / 4090 have 24GB VRAM they're both pretty decent fine tuning chips. I think you could probably fine-tune a model up to ~13B parameters on one of them with PEFT (https://github.com/huggingface/peft)
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Whisper prompt tuning
Hi everyone. Recently I've been looking into the PEFT library (https://github.com/huggingface/peft) and I was wondering if it would be possible to do prompt tuning with OpenAI's Whisper model. They have an example notebook for tuning Whisper with LoRA (https://colab.research.google.com/drive/1vhF8yueFqha3Y3CpTHN6q9EVcII9EYzs?usp=sharing) but I'm not sure how to go about changing it to use prompt tuning instead.
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Code Llama - The Hugging Face Edition
In the coming days, we'll work on sharing scripts to train models, optimizations for on-device inference, even nicer demos (and for more powerful models), and more. Feel free to like our GitHub repos (transformers, peft, accelerate). Enjoy!
- PEFT 0.5 supports fine-tuning GPTQ models
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Exploding loss when trying to train OpenOrca-Platypus2-13B
image
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[D] Is there a difference between p-tuning and prefix tuning ?
I discussed part of this here: https://github.com/huggingface/peft/issues/123
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How does using QLoRAs when running Llama on CPU work?
It seems like the merge_and_unload function in this PEFT script might be what they are referring to: https://github.com/huggingface/peft/blob/main/src/peft/tuners/lora.py
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How to merge the two weights into a single weight?
To obtain the original llama model, one may refer to this doc. To merge a lora model with a base model, one may refer to PEFT or use the merge script provided by LMFlow.
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[D] [LoRA + weight merge every N step] for pre-training?
you could use a callback, like show here, https://github.com/huggingface/peft/issues/286 and call code to merge them here.
ue5-llama-lora
Posts with mentions or reviews of ue5-llama-lora.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-06-26.
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[Request] A tracker for all 'useful' llama applications updated every week
https://github.com/bublint/ue5-llama-lora https://www.reddit.com/r/LocalLLaMA/comments/157vzq6/unleashing_the_power_of_language_learning_models/
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Training Pygmalion on a specific subject. Is it possible?
You can follow this guy's steps. https://github.com/bublint/ue5-llama-lora He basic just throw a txt file let AI read it. Pygmalion 7B or 13B are both llama base, so you can just follow his step to fine-tuning Pygmalion you want. You will need to prepare the character's script,like chat,reaction,background to a file,then just hope AI will learn it correctly,it might need to fine-tuning multiple times if your feed is not enough or AI learn it wrong somehow.
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What is the best way to create a knowledge-base specific LLM chatbot ?
ue5 lora might be a good starting point. It doesn't use any advanced features at all:
- Is there a way to fine-tune llama on extremely small dataset?
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Simplifying documentation navigation: here is UE5_documentalist, a personal project that provides a natural language query system
I got the idea from a reddit user that started a project that uses LLMs (forgot his name but here's a link to his repo, and I based my implementation from this TDS article
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Proof-of-concept with fine-tuning on local data?
Someone did a LoRA finetuning example using the UE5 documentation, which I replicated to make sure, and you do end up producing word patterns from the document, but it doesn't get incorporated as concepts very well
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Please explain to a 5 years old Lora concept and how to fine tune
GitHub - bublint/ue5-llama-lora: A proof-of-concept project that showcases the potential for using small, locally trainable LLMs to create next-generation documentation tools.
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Is what I need possible currently?
This would be an interesting experiment. People are already doing similar stuff, such as expanding the model's knowledge domain into something specific. Here's an example of how someone created a LoRA for UE5 documentation: https://github.com/bublint/ue5-llama-lora
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Can I train gpt4-x-alpaca with my own data?
I basically copied the steps from this Unreal Engine 5 LoRA repo and adjusted as needed.
- [P] Finetuning a commercially viable open source LLM (Flan-UL2) using Alpaca, Dolly15K and LoRA
What are some alternatives?
When comparing peft and ue5-llama-lora you can also consider the following projects:
lora - Using Low-rank adaptation to quickly fine-tune diffusion models.
AlpacaDataCleaned - Alpaca dataset from Stanford, cleaned and curated
LoRA - Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
h2o-llmstudio - H2O LLM Studio - a framework and no-code GUI for fine-tuning LLMs. Documentation: https://h2oai.github.io/h2o-llmstudio/
alpaca-lora - Instruct-tune LLaMA on consumer hardware
llama_farm - Use local llama LLM or openai to chat, discuss/summarize your documents, youtube videos, and so on.
dalai - The simplest way to run LLaMA on your local machine
ue5_documentalist - Turning the UE5 documentation to a searchable database
mlc-llm - Enable everyone to develop, optimize and deploy AI models natively on everyone's devices.
dolly - Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform
minLoRA - minLoRA: a minimal PyTorch library that allows you to apply LoRA to any PyTorch model.
llama - Inference code for Llama models