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Top 23 Python transfer-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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haystack
:mag: Haystack is an open source NLP framework to interact with your data using Transformer models and LLMs (GPT-4, ChatGPT and alike). Haystack offers production-ready tools to quickly build complex question answering, semantic search, text generation applications, and more.
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InfluxDB
Access the most powerful time series database as a service. Ingest, store, & analyze all types of time series data in a fully-managed, purpose-built database. Keep data forever with low-cost storage and superior data compression.
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Project mention: pip install remyxai - easiest way to create custom vision models | /r/computervision | 2023-04-25
This seems not very convincing. There are other popular frameworks that provide AutoML with existing datasets (eg https://github.com/autogluon/autogluon)
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super-gradients
Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.
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Transfer-Learning-Library
Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization
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FARM
:house_with_garden: Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering.
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Sonar
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Project mention: Any recommendation for the replacement of the toolkit jiant? [Research] [Discussion] | /r/MachineLearning | 2022-06-11
I am doing research in NLP with the toolkit jiant (https://github.com/nyu-mll/jiant). It is a quite nice and easy-to-use tool. Unfortunately, it stopped being maintained. I wonder is there any other recommendation that I can use to replace it?
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flow-forecast
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
-Flow
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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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image-background-remove-tool
✂️ Automated high-quality background removal framework for an image using neural networks. ✂️
Project mention: Show HN: Image background removal without annoying subscriptions | news.ycombinator.com | 2023-05-25 -
deepdrive
Deepdrive is a simulator that allows anyone with a PC to push the state-of-the-art in self-driving
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primeqa
The prime repository for state-of-the-art Multilingual Question Answering research and development.
Project mention: Natural language, chat-based, AI-assisted search for Gmail | /r/SomebodyMakeThis | 2023-03-08Look into primeqa (github/primeqa. With some basic python programming you can do alot of things!!
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pykale
Knowledge-Aware machine LEarning (KALE): accessible machine learning from multiple sources for interdisciplinary research, part of the 🔥PyTorch ecosystem
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assembled-cnn
Tensorflow implementation of "Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network"
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Project mention: [D] Difference between [ Offsite-Tuning: Transfer Learning without Full Model ] and Federated learning? | /r/MachineLearning | 2023-02-19
Found relevant code at https://github.com/mit-han-lab/offsite-tuning + all code implementations here
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Project mention: PyTorch-adapt re-purposes existing ML models to work in new domains | news.ycombinator.com | 2022-11-30
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You're pretty much right on the money. For ParaCrawl[1] (which I worked on) we used fast machine translation systems that were "good enough" to translate one side of each pair to the language of the other, see whether they'd match sufficiently, and then deal with all the false positives through various filtering methods. Other datasets I know of use multilingual sentence embeddings, like LASER[2], to compute the distance between two sentences.
Both of these methods have a bootstrapping problem, but at this point in the MT for many languages we have enough data to get started. Previous iterations of ParaCrawl used things like document structure and overlap of named entities among sentences to identify matching pairs. But this is much less robust. I don't know how they solve this problem today for low-resource languages.
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Python transfer-learning related posts
- Partial Solution To AI Hallucinations
- Show HN: Haystack NLP Now Supports GPT4 with PromptNode and Agent
- Haystack: An NLP Framework to Use Transformers in Your Applications
- Build LLM-Based Agents Yourself with Open Source
- [D] GPT Question Answering with Reasoning
- I build an open-source google-like search for workplace knowledge
- Announcing GPT-4.
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A note from our sponsor - Sonar
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Index
What are some of the best open-source transfer-learning projects in Python? This list will help you:
Project | Stars | |
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1 | transferlearning | 11,519 |
2 | haystack | 8,976 |
3 | autogluon | 5,799 |
4 | hub | 3,342 |
5 | super-gradients | 2,672 |
6 | Transfer-Learning-Library | 2,570 |
7 | FARM | 1,667 |
8 | transfer-learning-conv-ai | 1,636 |
9 | jiant | 1,520 |
10 | flow-forecast | 1,465 |
11 | finetuner | 1,073 |
12 | image-background-remove-tool | 916 |
13 | deepdrive | 836 |
14 | primeqa | 546 |
15 | DeepFake-Detection | 394 |
16 | pykale | 386 |
17 | assembled-cnn | 329 |
18 | test | 297 |
19 | offsite-tuning | 292 |
20 | pytorch-adapt | 270 |
21 | xfer | 250 |
22 | kiri | 238 |
23 | laserembeddings | 205 |