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Top 16 Python few-shot-learning Projects
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transferlearning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
Project mention: [D] Medium Article: Adaptive Learning for Time Series Forecasting | /r/MachineLearning | 2022-10-02The src is available in https://github.com/jindongwang/transferlearning I'll also publish about how to code the model for time series
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Awesome-Prompt-Engineering
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
Yes, there are a lot of different resources online, especially for generative AI. The Awesome Prompt Engineering github is probably a good place to start https://github.com/promptslab/Awesome-Prompt-Engineering. If you're focusing directly on OpenAI's models then the OpenAI Prompt Engineering Guide would be my recommendation https://help.openai.com/en/articles/6654000-best-practices-for-prompt-engineering-with-openai-api.
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Mergify
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Project mention: How do you think search will change with technology like ChatGPT, Bing’s new AI search engine and the upcoming Google Bard? | /r/singularity | 2023-02-21
And all of that has something to do with finetuners. It basically fine-tunes AI models for specific use cases. With it can create a custom search experience that is tailored to their specific needs. I also wonder how this is going to be integrated into SEO tools soon since those tools are catered to traditional search engines.
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MMFewShot: OpenMMLab fewshot learning toolbox and benchmark.
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Project mention: [Colab Notebook] Launch quantized MPT-30B-Chat on Vast.ai using text-generation-inference, integrated with ConversationChain | /r/LangChain | 2023-07-09
One method for comparison is the MMLU https://arxiv.org/abs/2009.03300.
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Project mention: Prompt Engineering Guide: Guides, papers, and resources for prompt engineering | news.ycombinator.com | 2023-02-21
Using the terminology that I'm working with this is an example of a second-order analytic augmentation!
Here's another approach of second-order analytic augmentation, PAL: https://reasonwithpal.com
And third-order, Toolformer: https://arxiv.org/abs/2302.04761
The difference isn't in what is going on but rather with framing the approach within the analytic-synthetic distinction developed by Kant and the analytic philosophers who were influenced by his work. There's a dash of functional programming thrown in for good measure!
I have scribbled on a print-out of the article on my desk:
Nth Order -
InfluxDB
Collect and Analyze Billions of Data Points in Real Time. Manage all types of time series data in a single, purpose-built database. Run at any scale in any environment in the cloud, on-premises, or at the edge.
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HugNLP
HugNLP is a unified and comprehensive NLP library based on HuggingFace Transformer. Please hugging for NLP now!😊 (by HugAILab)
Project mention: HugNLP: A Unified and Comprehensive Open-Source Library for NLP | news.ycombinator.com | 2023-05-03 -
self-refine
LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.
Project mention: ChemCrow: Augmenting large-language models with chemistry tools | news.ycombinator.com | 2023-04-17>the systems operation are well understood
That's like saying human behavior is well understood because we know how neurons communicate signals. It's too low level to be useful, hence psychology.
>They don't have the ability to reason or reflect.
Yes they do
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Project mention: Allen Institute for Artificial Intelligence Introduces MemPrompt: A New Method to “fix” GPT-3 After Deployment with User Interaction | /r/machinelearningnews | 2022-12-18
Quick Read: https://www.marktechpost.com/2022/12/18/allen-institute-for-artificial-intelligence-introduces-memprompt-a-new-method-to-fix-gpt-3-after-deployment-with-user-interaction/ Paper: https://arxiv.org/abs/2201.06009 Code: https://github.com/madaan/memprompt
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Project mention: A transformer-based method for zero and few-shot biomedical NER | news.ycombinator.com | 2023-05-12
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HugNLP
HugNLP is a unified and comprehensive NLP library based on HuggingFace Transformer. Please hugging for NLP now!😊 HugNLP will released to @HugAILab
Project mention: HugNLP: A Unified and Comprehensive Library for Natural Language Processing | news.ycombinator.com | 2023-04-13 -
deep-kernel-transfer
Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)
Project mention: What approach to take predicting a simple data stream? | /r/neuralnetworks | 2022-10-03Interesting approach to small datasets. Here is an implementation I'll look at: https://github.com/BayesWatch/deep-kernel-transfer
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ORBIT-Dataset
The ORBIT dataset is a collection of videos of objects in clean and cluttered scenes recorded by people who are blind/low-vision on a mobile phone. The dataset is presented with a teachable object recognition benchmark task which aims to drive few-shot learning on challenging real-world data.
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While it's a bit of an overkill, prompt-lib provides a notebook to do this: https://github.com/reasoning-machines/prompt-lib/blob/main/notebooks/QueryOpenAI.ipynb
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Sonar
Write Clean Python Code. Always.. Sonar helps you commit clean code every time. With over 225 unique rules to find Python bugs, code smells & vulnerabilities, Sonar finds the issues while you focus on the work.
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
The latest post mention was on 2023-07-09.
Python few-shot-learning related posts
- Remote Work 2.0: The Tools, Trends, and Challenges of the Post-Pandemic Work Era
- [Colab Notebook] Launch quantized MPT-30B-Chat on Vast.ai using text-generation-inference, integrated with ConversationChain
- A transformer-based method for zero and few-shot biomedical NER
- AI lessons
- Partial Solution To AI Hallucinations
- HugNLP: A Unified and Comprehensive Open-Source Library for NLP
- [D] A model to extract relevant information from a Sample Ballot.
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A note from our sponsor - Mergify
blog.mergify.com | 22 Sep 2023
Index
What are some of the best open-source few-shot-learning projects in Python? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | transferlearning | 11,956 |
| 2 | Awesome-Prompt-Engineering | 2,140 |
| 3 | FSL-Mate | 1,550 |
| 4 | finetuner | 1,187 |
| 5 | mmfewshot | 593 |
| 6 | test | 538 |
| 7 | pal | 368 |
| 8 | HugNLP | 332 |
| 9 | self-refine | 320 |
| 10 | memprompt | 310 |
| 11 | zshot | 262 |
| 12 | HugNLP | 240 |
| 13 | deep-kernel-transfer | 183 |
| 14 | TaiChi | 79 |
| 15 | ORBIT-Dataset | 78 |
| 16 | prompt-lib | 71 |
Write Clean Python Code. Always.
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