nn
GFPGAN-for-Video-SR
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nn | GFPGAN-for-Video-SR | |
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26 | 1 | |
48,004 | 31 | |
8.5% | - | |
7.7 | 0.0 | |
about 1 month ago | 10 months ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | - |
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nn
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Can't remember name of website that has explanations side-by-side with code
Hey are you talking about https://nn.labml.ai/ ?
- [D] Recent ML papers to implement from scratch
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[P] GPT-NeoX inference with LLM.int8() on 24GB GPU
Implementation & LM Eval Harness Results
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[P] Fine-tuned the GPT-Neox Model to Generate Quotes
Github: https://github.com/labmlai/annotated_deep_learning_paper_implementations/tree/master/labml_nn/neox
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Best resources to learn recent transformer papers and stay updated [D]
Regarding implementations this helps me: https://nn.labml.ai/
- Introductory papers to implement
- How to convert research papers to code?
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[D] How to convert papers to code?
Dunno if this is directly helpful, but this website has implementation with the math side by side https://nn.labml.ai/
- [D] Looking for open source projects to contribute
- Resource for papers explanation
GFPGAN-for-Video-SR
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I Upscaled Linus's first video (Better results than Topaz Labs)
If you want to upscale your own videos , check out my colab notebook to do it for free : https://github.com/GeeveGeorge/GFPGAN-for-Video-SR
What are some alternatives?
labml - 🔎 Monitor deep learning model training and hardware usage from your mobile phone 📱
Real-ESRGAN-Video-Batch-Process - Upscale any number of videos using this colab notebook!
functorch - functorch is JAX-like composable function transforms for PyTorch.
ganspace - Discovering Interpretable GAN Controls [NeurIPS 2020]
ZoeDepth - Metric depth estimation from a single image
gan-vae-pretrained-pytorch - Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.
onnx-simplifier - Simplify your onnx model
License-super-resolution - A License Plate Image Reconstruction Project in Tensorflow2
Basic-UI-for-GPT-J-6B-with-low-vram - A repository to run gpt-j-6b on low vram machines (4.2 gb minimum vram for 2000 token context, 3.5 gb for 1000 token context). Model loading takes 12gb free ram.
Real-ESRGAN-ncnn-vulkan - NCNN implementation of Real-ESRGAN. Real-ESRGAN aims at developing Practical Algorithms for General Image Restoration.
Behavior-Sequence-Transformer-Pytorch - This is a pytorch implementation for the BST model from Alibaba https://arxiv.org/pdf/1905.06874.pdf
DFL-Colab - DeepFaceLab fork which provides IPython Notebook to use DFL with Google Colab