notebooks
Magpie-Recycling-Project
notebooks | Magpie-Recycling-Project | |
---|---|---|
17 | 4 | |
3,293 | 16 | |
2.7% | - | |
8.4 | 0.0 | |
4 days ago | over 2 years ago | |
Jupyter Notebook | Python | |
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
đź““ 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
Magpie-Recycling-Project
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We have developed a bird feeder where birds can exchange litter for food
Given their code: no, it just detects whether anything has been dropped in. Most likely they trained the magpies to drop trash by putting "examples" around the drop hole and the magpies continued to bring more. Magpies are known to collect colorful and shiny trinkets and bring them to their nest, so it's already in their nature.
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Wild birds use litter vending machine
GitHub.
What are some alternatives?
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
notebooks - Jupyter notebooks for the Natural Language Processing with Transformers book
Transformers-Tutorials - This repository contains demos I made with the Transformers library by HuggingFace.
stable-diffusion - k_diffusion wrapper included for k_lms sampling. fixed for notebook.
easydiffusion - Easy Diffusion is an advanced Stable Diffusion Notebook with a feature rich image processing suite.
stable-diffusion-colab - Adapdet for google colab
HidamariDiffusionColab - colab for stable diffusion
diffusers - 🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch
huggingface_hub - The official Python client for the Huggingface Hub.
ai-notebooks - Various ai notebooks
easydiffusion - Easiest 1-click way to create beautiful artwork on your PC using AI, with no tech knowledge. Provides a browser UI for generating images from text prompts and images. Just enter your text prompt, and see the generated image.
doohickey - Doohickey is a stable diffusion tool for technical artists who want to stay up-to-date with the latest developments in the field.