minLoRA Alternatives

Similar projects and alternatives to minLoRA based on common topics and language

langchain

152 56,526 10.0 Python minLoRA VS langchain

Discontinued ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain] (by hwchase17)
peft

26 13,783 9.7 Python minLoRA VS peft

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
WorkOS

workos.com sponsored

The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
GTSRB

1 108 10.0 Jupyter Notebook minLoRA VS GTSRB

Convolutional Neural Network for German Traffic Sign Recognition Benchmark
labml

23 1,867 9.7 Jupyter Notebook minLoRA VS labml

🔎 Monitor deep learning model training and hardware usage from your mobile phone 📱
fastai

9 25,610 8.0 Jupyter Notebook minLoRA VS fastai

The fastai deep learning library
tsai

4 4,690 7.4 Jupyter Notebook minLoRA VS tsai

Time series Timeseries Deep Learning Machine Learning Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai
SkinDeep

16 930 3.1 Jupyter Notebook minLoRA VS SkinDeep

Get Deinked!!
InfluxDB

www.influxdata.com sponsored

Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better minLoRA alternative or higher similarity.

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minLoRA reviews and mentions

Posts with mentions or reviews of minLoRA. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-11.

[D] Is it possible to train the same LLM instance on different users' data?
2 projects | /r/MachineLearning | 11 Apr 2023

This repository seems to be doing it. Basically, you want to take the weights/biases that were trained during the LoRA training process and include them in the compute graph for the larger network, or remove them.
[P] minLoRA: An Easy-to-Use PyTorch Library for Applying LoRA to PyTorch Models
3 projects | /r/MachineLearning | 21 Feb 2023

Theirs requires you to rewrite the whole model and replace every layer you want to apply LoRA to to the LoRA counterpart, or use monky-patching. Mine utilizes PyTorch parametrizations to inject the LoRA logic to existing models. If your model has nn.Linear, you can call add_lora(model) to add LoRA to all the linear layers. And it's not limited to Linear, you can see how I extended it to Embedding, Conv2d in a couple lines of code. https://github.com/cccntu/minLoRA/blob/main/minlora/model.py