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The notebooks for generative AI by using PyTorch, Huggingface/diffusers, transforms. And the implementing of the algorithms in paper

Home Page: https://www.kaggle.com/aisuko/code

License: Apache License 2.0

Jupyter Notebook 99.99% Makefile 0.01%
diffusers kaggle mps pytorch applemetal neural-network convolutional-neural-networks collaborate github hacktoberfest2023

generative-ai's Introduction

Diffusion

No Title Open in Studio Lab Open in Kaggle Open in Colab
1 Deconstruct the Stable Diffusion pipeline Open in SageMaker Studio Lab Kaggle Colab
2 Basic training model Kaggle Colab
3 Deconstruct the basic pipeline Kaggle
4 Details for models and schedulers Kaggle
5 Effective and Efficient diffusion Kaggle
6 Generting by using float16(sppeding up) Kaggle
7 Stable Diffusion v1.5 demo Kaggle
8 Load checkpoints models and schedulers Kaggle
9 Schedulers Performance Kaggle
10 Stable diffusion with diffusers Kaggle

Implementation

No Title Open in Studio Lab Open in Kaggle Open in Colab Paper
1 The annotated diffusion model Kaggle 1503.03585,1907.05600,2006.11239
2 QLoRA Fine-tuning for Falcon-7B with PEFT Being reviewed

PyTorch Fundamentals

On Kaggle

Many of the notebooks are executed on Kaggle

No Title Open in Kaggle
1 Segment Anything Model Kaggle
2 CTransformers Kaggle

On macOS

All the notebooks are support mps, except if the notebooks import fp16 speeding up:

mps

Contributing

Warm welcome for any contributions, please follow the contributing guidelines.

Credit

generative-ai's People

Contributors

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Stargazers

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generative-ai's Issues

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