SaaSHub helps you find the best software and product alternatives Learn more β
Top 12 Python instruction-tuning Projects
-
InfluxDB
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.
-
Otter
𦦠Otter, a multi-modal model based on OpenFlamingo (open-sourced version of DeepMind's Flamingo), trained on MIMIC-IT and showcasing improved instruction-following and in-context learning ability.
-
WorkOS
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.
-
HugNLP
CIKM2023 Best Demo Paper Award. HugNLP is a unified and comprehensive NLP library based on HuggingFace Transformer. Please hugging for NLP now!π (by HugAILab)
-
tasksource
Datasets collection and standardization preprocessings for NLP extreme multitask learning
Depends what model you want to train, and how well you want your computer to keep working while you're doing it.
If you're interested in large language models there's a table of vram requirements for fine-tuning at [1] which says you could do the most basic type of fine-tuning on a 7B parameter model with 8GB VRAM.
You'll find that training takes quite a long time, and as a lot of the GPU power is going on training, your computer's responsiveness will suffer - even basic things like scrolling in your web browser or changing tabs uses the GPU, after all.
Spend a bit more and you'll probably have a better time.
[1] https://github.com/hiyouga/LLaMA-Factory?tab=readme-ov-file#...
Hereβs another one - itβs older but has some interesting charts and graphs.
https://arxiv.org/abs/2303.18223
Project mention: OpenAI vs Google, Detect ChatGPT Content with 99% accuracy, Navigating AI compute costs | /r/ChatGPT | 2023-06-15π Video-LLaMA - Empower large language models with video and audio understanding capability. (link) 𦦠Otter - Multi-modal model with improved instruction-following and in-context learning ability. π Linkly.AI - AI-powered lead analytics and management platform that helps you track, analyze, and streamline your leads in one place. π¬ Jet Cut Ready - AI plugin for Adobe Premiere Pro that automatically removes silent parts in videos. (link) π¬ HeyGen's ChatGPT Plugin - Convert text into high-quality videos using AI text and video generation.
Project mention: Show HN: NExT-GPT β First LLM working with multimodal input and output | news.ycombinator.com | 2023-09-21
Project mention: Unleash the Power of Video-LLaMA: Revolutionizing Language Models with Video and Audio Understanding! | dev.to | 2023-06-12We extend our deepest gratitude to the extraordinary projects that have influenced and contributed to the development of Video-LLaMA. We're indebted to MiniGPT-4, FastChat, BLIP-2, EVA-CLIP, ImageBind, LLaMA, VideoChat, LLaVA, WebVid, and mPLUG-Owl for their invaluable contributions. Special thanks to Midjourney for creating the stunning Video-LLaMA logo, encapsulating the essence of our groundbreaking project.
Project mention: HugNLP: A Unified and Comprehensive Open-Source Library for NLP | news.ycombinator.com | 2023-05-03
Technically, BERT (bert-base) is not sota anymore. deberta+MTT-DNN (multi-task learning on many datasets) https://ibm.github.io/model-recycling/ is arguably sota.
Python instruction-tuning related posts
- Google Bard AI Now Has the Ability to Understand YouTube Videos
- Video-LLaVA
- Video-LLaVA
- Share your favorite materials: intersection of LLMs and business applications
- Recommended open LLMs with image input modality?
- HugNLP: A Unified and Comprehensive Open-Source Library for NLP
- [R] CodeCapybara: Another open source model for code generation based on instruction tuning, outperformed Llama and CodeAlpaca
-
A note from our sponsor - SaaSHub
www.saashub.com | 29 Apr 2024
Index
What are some of the best open-source instruction-tuning projects in Python? This list will help you:
Project | Stars | |
---|---|---|
1 | LLaMA-Factory | 20,248 |
2 | LLMSurvey | 8,716 |
3 | self-instruct | 3,666 |
4 | Otter | 3,447 |
5 | NExT-GPT | 2,860 |
6 | Video-LLaVA | 2,368 |
7 | mPLUG-Owl | 1,945 |
8 | InternVideo | 909 |
9 | DataDreamer | 632 |
10 | HugNLP | 370 |
11 | CodeCapybara | 156 |
12 | tasksource | 122 |
Sponsored