Add cog.yaml and predict.py for usage with Replicate and Docker #39
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- Add time tracking for image generation - Save multiple images from a list of prompts - Calculate and display average time per image - Improve code readability and organization
Collaborator
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That is amazing. I will review your pr to see if it is appropriate in this repo. Thanks for your contributions! |
- Implement login and logout functionality - Enhance security with password hashing - Address issue nunchaku-tech#42 for user access control
- Include safety_checker module for NSFW detection - Adjust server.py to use safety checker with adjustable sensitivity - Modify Dockerfile to copy safety_checker directory - Update server command to use module syntax
Author
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I have now modified the branch to work directly with Docker. If you are interested in the Docker stuff without the replicate/cog things I could clean this PR up. |
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Did cog end up shipping? I think it's a really awesome feature because it provides a deployment option, with API and queue out of the box. |
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I'm not totally sure if you want to have this in your repository but I figured I'd make a pull request anyway.
This PR adds the necessary configuration and code to deploy the model on Replicate:
cog.yamlwith CUDA 12.4 and Python 3.11 setuppredict.pywith Replicate-compatible inference codeexample.pywith batch processing supportThe implementation supports configurable image dimensions, inference steps, and seeds. Sequential CPU offloading is enabled by default for better memory management.
Let me know if you need any clarification or changes.
It is deployed here: https://replicate.com/pollinations/flux-schnell-svdquant