diffusion-models-class
tutorials
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| diffusion-models-class | tutorials | |
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diffusion-models-class
- diffusion low level question
- Here's a learning resource
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[R] Classifier-Free Guidance can be applied to LLMs too. It generally gives results of a model twice the size you apply it to. New SotA on LAMBADA with LLaMA-7B over PaLM-540B and plenty other experimental results.
When you use stable diffusion, you can adjust the classifier free guidance scale to control how much it follows the input prompt. From what I understand(check https://github.com/huggingface/diffusion-models-class/tree/main/unit3), what cfg does is that it generates an unconditional image and an image conditional on the text prompt, and then scale up the difference.
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Ai Coding roadmap
https://huggingface.co/learn/nlp-course/ https://huggingface.co/docs/transformers (go through the task guide) https://github.com/huggingface/diffusion-models-class http://d2l.ai/ https://www.youtube.com/watch?v=VMj-3S1tku0&list=PLAqhIrjkxbuWI23v9cThsA9GvCAUhRvKZ
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How does stable diffusion work from a technical perspective?
I couldn't understand the original paper(havent done meth in a long time). This blog post and short course help me to understand.
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Using SD programatically with APIs
The Diffusion Models Course is another good resource to learn more technical details.
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I made a generative 3D game and took a walk in the streets of Paris. Playback speed 30x
Next, you need to become familiar with the diffusion model. I recommend this huggingface's course(https://github.com/huggingface/diffusion-models-class) because it is very high quality and you will learn while using diffusers. At first glance, it may not seem directly related to this game, but in my case, knowing what is happening in diffusers helped me in many ways: trial and error, inspiration for ideas, etc. I had no knowledge of pytorch (the deep learning library used for diffusers), so I also took this course (https://www.udacity.com/course/deep-learning-pytorch--ud188) which was in the prerequisites for that huggingface's course. It was also very good.
- Sunt AI Research Scientist, AMA
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Dreambooth Hackaton: How can we use a text-to-image model to explore the cinematographic appeal of Torres del Paine 🇨🇱?
Hugging Face Dreambooth Hackaton details
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[N] Personalise Stable Diffusion models in DreamBooth Hackathon
Details: https://github.com/huggingface/diffusion-models-class/blob/main/hackathon/README.md
tutorials
What are some alternatives?
deforum-stable-diffusion
MovieRecommender - 🎥 Movie Recommender AI System
UnstableFusion - A Stable Diffusion desktop frontend with inpainting, img2img and more!
pml-book - "Probabilistic Machine Learning" - a book series by Kevin Murphy
approachingalmost - Approaching (Almost) Any Machine Learning Problem
Emotions-Classification - Tells You about the emotion/Sentimental Analysis of a Sentence
manim-tutorial - Manim tutorial presented to PhD and Master student at UCLouvain
deforumed-walk - Take a walk in the generated world.
EverythingCrypto - (Still exploring) My cryptography journey: A collection of notebooks covering different algorithms and concepts from cryptography
sd-webui-controlnet - WebUI extension for ControlNet
pyspark-tutorial - PySpark Tutorial for Beginners - Practical Examples in Jupyter Notebook with Spark version 3.4.1. The tutorial covers various topics like Spark Introduction, Spark Installation, Spark RDD Transformations and Actions, Spark DataFrame, Spark SQL, and more. It is completely free on YouTube and is beginner-friendly without any prerequisites.