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Top 23 pretrained-model Open-Source Projects
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pytorch-image-models
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNet-V3/V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
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InfluxDB
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PaddleNLP
👑 Easy-to-use and powerful NLP and LLM library with 🤗 Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including 🗂Text Classification, 🔍 Neural Search, ❓ Question Answering, ℹ️ Information Extraction, 📄 Document Intelligence, 💌 Sentiment Analysis etc.
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Qwen
The official repo of Qwen (通义千问) chat & pretrained large language model proposed by Alibaba Cloud.
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petals
🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
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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.
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LMFlow
An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All.
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pyannote-audio
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
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silero-models
Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple
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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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awesome-pretrained-chinese-nlp-models
Awesome Pretrained Chinese NLP Models，高质量中文预训练模型&大模型&多模态模型&大语言模型集合
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facenet-pytorch
Pretrained Pytorch face detection (MTCNN) and facial recognition (InceptionResnet) models
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Efficient-AI-Backbones
Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
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Chinese-CLIP
Chinese version of CLIP which achieves Chinese cross-modal retrieval and representation generation.
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PINTO_model_zoo
A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.
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SaaSHub
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Project mention: Maxtext: A simple, performant and scalable Jax LLM | news.ycombinator.com | 2024-04-23Is t5x an encoder/decoder architecture?
Some more general options.
The Flax ecosystem
https://github.com/google/flax?tab=readme-ov-file
or dm-haiku
https://github.com/google-deepmind/dm-haiku
were some of the best developed communities in the Jax AI field
Perhaps the “trax” repo? https://github.com/google/trax
Some HF examples https://github.com/huggingface/transformers/tree/main/exampl...
Sadly it seems much of the work is proprietary these days, but one example could be Grok-1, if you customize the details. https://github.com/xai-org/grok-1/blob/main/run.py
virtual dj and others stem separator is shrinked model of this https://github.com/deezer/spleeter you will get better results downloading original + their large model.
Qwen: https://github.com/QwenLM/Qwen
Project mention: Instance segmentation of small objects in grainy drone imagery | /r/computervision | 2023-12-09Also, I’d suggest considering switching to the segmentation-models library - it provides U-Net models with a variety of pretrained backbones of as encoders. The author also put out a PyTorch version. https://github.com/qubvel/segmentation_models.pytorch https://github.com/qubvel/segmentation_models
So how long until we can do an open source Mistral Large?
We could make a start on Petals or some other open source distributed training network cluster possibly?
[0] https://petals.dev/
While OpenAI’s CLIP model has garnered a lot of attention, it is far from the only game in town—and far from the best! On the OpenCLIP leaderboard, for instance, the largest and most capable CLIP model from OpenAI ranks just 41st(!) in its average zero-shot accuracy across 38 datasets.
Project mention: For Developers - THUDM/CodeGeeX: CodeGeeX: An Open Multilingual Code Generation Model | /r/OfflineAI | 2023-05-20
pyannote/pyannote-audio
CogVLM is very good in my (brief) testing: https://github.com/THUDM/CogVLM
The model weights seem to be under a non-commercial license, not true open source, but it is "open access" as you requested.
Project mention: Weird A.I. Yankovic, a cursed deep dive into the world of voice cloning | news.ycombinator.com | 2023-10-02I doubt it's currently actually "the best open source text to speech", but the answer I came up with when throwing a couple of hours at the problem some months ago was "Silero" [0, 1].
Following the "standalone" guide [2], it was pretty trivial to make the model render my sample text in about 100 English "voices" (many of which were similar to each other, and in varying quality). Sampling those, I got about 10 that were pretty "good". And maybe 6 that were the "best ones" (pretty natural, not annoying to listen to).
IIRC the license was free for noncommercial use only. I'm not sure exactly "how open source" they are, but it was simple to install the dependencies and write the basic Python to try it out; I had to write a for loop to try all the voices like I wanted. I ended using something else for the project for other reasons, but this could still be fairly good backup option for some use cases IMO.
[0] https://github.com/snakers4/silero-models#text-to-speech
Most computer vision models are trained to predict on a preset list of label classes. In object detection, for instance, many of the most popular models like YOLOv8 and YOLO-NAS are pretrained with the classes from the MS COCO dataset. If you download the weights checkpoints for these models and run prediction on your dataset, you will generate object detection bounding boxes for the 80 COCO classes.
Hijacking this comment because i've been working nonstop on my project thanks to your suggestion. I'm now using this https://github.com/derronqi/yolov8-face for face detection and still the old face_recognition for encodings. I'm clustering with dbscan and extracting frames with ffmpeg with -hwaccel on. I'm planning to try this: https://github.com/timesler/facenet-pytorch as it looks like it would be the fastest thing avaiable to process videos? Keep in mind i need to perform encoding other than just detection because i want to use DBscan (and later also facial recognition, but this might be done separately just by saving the encodings). let me know if you have any other suggestions, and thanks again for your help
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).
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Index
What are some of the best open-source pretrained-model projects? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | transformers | 125,021 |
| 2 | pytorch-image-models | 29,751 |
| 3 | spleeter | 24,878 |
| 4 | PaddleNLP | 11,386 |
| 5 | Qwen | 10,893 |
| 6 | segmentation_models.pytorch | 8,800 |
| 7 | petals | 8,661 |
| 8 | open_clip | 8,391 |
| 9 | LMFlow | 8,000 |
| 10 | CodeGeeX | 7,751 |
| 11 | EfficientNet-PyTorch | 7,715 |
| 12 | mmf | 5,415 |
| 13 | PaddleClas | 5,251 |
| 14 | pyannote-audio | 5,027 |
| 15 | CogVLM | 4,968 |
| 16 | silero-models | 4,534 |
| 17 | super-gradients | 4,322 |
| 18 | awesome-pretrained-chinese-nlp-models | 4,193 |
| 19 | facenet-pytorch | 4,144 |
| 20 | Efficient-AI-Backbones | 3,783 |
| 21 | Chinese-CLIP | 3,590 |
| 22 | PINTO_model_zoo | 3,288 |
| 23 | mmpretrain | 3,156 |
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