notebooks
pytorch-image-models
notebooks | pytorch-image-models | |
---|---|---|
17 | 35 | |
3,293 | 29,828 | |
2.7% | 1.2% | |
8.4 | 9.4 | |
4 days ago | 2 days ago | |
Jupyter Notebook | Python | |
Apache License 2.0 | Apache License 2.0 |
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notebooks
- Training multiple models like ResNet50 or ViT on the same dataset [P]
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Sagemaker Model deployment and Integration
📓 Open the notebook for an example of how to run a batch transform job for inference.
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Your own Stable Diffusion endpoint with AWS SageMaker
In order to overwrite it, the package readme has some general information about it, and also there is an example in this jupyter notebook. We are doing what is necessary via the files inside sagemaker/code, which has the inference code following SageMaker requirements, and a requirements.txt, that has the necessary dependencies that will be installed when the endpoint gets created
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Is there a huggingface model that does free response QA?
You still haven’t explained your use-case for the model. You can look up “Open Domain QA” models. There are a lot of them, but they’re often restricted in how well they generalize and benefit from fine tuning. E.g., https://github.com/huggingface/notebooks/blob/main/longform-qa/Long_Form_Question_Answering_with_ELI5_and_Wikipedia.ipynb
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List of Stable Diffusion systems - Part 3
(Updated Aug. 27, 2022) Colab notebook Stable Diffusion with diffusers by huggingface. GitHub repo. Video tutorial. Official Colab notebook. txt2img. Uses HuggingFace diffusers repo.
- anyone having issues with the textual inversion colab?
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Training textual inversion of Stable Diffusion on your own dataset
Looks like they updated the notebook 15 minutes ago. Hopefully it works now.
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Ask HN: What kind of data do I need to build a language model?
Basically, you can then do similar things using HuggingFace, as indeed many have (you can explore the models in their hub)[2]
[1] https://www.youtube.com/playlist?list=PLtmWHNX-gukKocXQOkQju...
[2] https://github.com/huggingface/notebooks/blob/main/examples/...
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[D] NLP has HuggingFace, what does Computer Vision have?
image classification: ViT, DeiT, BEiT, Swin Transformer, PoolFormer, ResNet, RegNet, ConvNeXT, Perceiver, ImageGPT, VAN. Check out the official example scripts, example notebooks.
- Need help in extracting a binary label from a text corpus
pytorch-image-models
- FLaNK AI Weekly 18 March 2024
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[D] Hugging face and Timm
I am a PyTorch user I work in CV, I usually use the PyTorch models. However, I see people use timm in research papers to train their models I don't understand what it is timm is it a new framework like PyTorch? Further, when I click https://pypi.org/project/timm/ homepage it takes me to hugging face GitHub https://github.com/huggingface/pytorch-image-models is there any connection between timm and hugging face many of my friends use hugging face but I also don't know about hugging face I use simple PyTorch and torchvision.models.
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FLaNK Stack Weekly for 07August2023
https://github.com/huggingface/pytorch-image-models https://huggingface.co/docs/timm/index
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[R] Nvidia RTX 4090 ML benchmarks. Under QEMU/KVM. Image + Transformers. FP16/FP32.
pytorch-image-models
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Inference on resent, cant work out the problem?
additionally, you might find the timm library handy for this sort of work.
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Swin Transformer: Hierarchical Vision Transformer Using Shifted Windows
This is still being pursued. Ross Wightmann's timm[0,1] package (now on Hugging Face) has done a lot of this. There's also a V2 of ConvNext[2]. Ross does write about this a lot on Twitter fwiw. I should also mention that there are still many transformer based networks that still beat convs. So there probably won't be a resurgence in convs until someone can show that there's a really strong reason for them. They have some advantages but they also might not be flexible enough for the long range tasks in segmentation and detection. But maybe they are.
FAIR definitely did great work with ConvNext, and I do hope to see more. There always needs to be people pushing unpopular paradigms.
[0] https://github.com/huggingface/pytorch-image-models
[1] https://arxiv.org/abs/2110.00476
[2] https://arxiv.org/abs/2301.00808
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Problems with Learning Rate Finder in Pytorch Lightning
I am doing Binary classification with a pre-trained EfficientNet tf_efficientnet_l2. I froze all weights during training and replaced the classifier with a custom trainable one that looks like:
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PyTorch at the Edge: Deploying Over 964 TIMM Models on Android with TorchScript and Flutter
In this post, I’m going to show you how you can pick from over 900+ SOTA models on TIMM, train them using best practices with Fastai, and deploy them on Android using Flutter.
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ImageNet Advise
The other thing is, try to find tricks to speed up your experiments (if not having done so already). The most obvious are mixed precision training, have your model train on a lower resolution input first and then increase the resolution later in the training, stochastic depth, and a bunch more stuffs. Look for implementations in https://github.com/rwightman/pytorch-image-models .
- Doubt about transformers
What are some alternatives?
Transformers-Tutorials - This repository contains demos I made with the Transformers library by HuggingFace.
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
stable-diffusion - k_diffusion wrapper included for k_lms sampling. fixed for notebook.
mmdetection - OpenMMLab Detection Toolbox and Benchmark
easydiffusion - Easy Diffusion is an advanced Stable Diffusion Notebook with a feature rich image processing suite.
detectron2 - Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
stable-diffusion-colab - Adapdet for google colab
mmcv - OpenMMLab Computer Vision Foundation
HidamariDiffusionColab - colab for stable diffusion
segmentation_models.pytorch - Segmentation models with pretrained backbones. PyTorch.
diffusers - 🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch
yolact - A simple, fully convolutional model for real-time instance segmentation.