Convert a Stable Diffusion XL checkpoint to Diffusers and open a PR
Visualize model performance on function calling tasks
View RL Benchmark Reports
GIFT-Eval: A Benchmark for General Time Series Forecasting
Benchmark models using PyTorch and OpenVINO
Calculate GPU requirements for running LLMs
Benchmark AI models by comparison
Multilingual Text Embedding Model Pruner
Explore and submit models using the LLM Leaderboard
Create and manage ML pipelines with ZenML Dashboard
Browse and submit LLM evaluations
Compare and rank LLMs using benchmark scores
Calculate survival probability based on passenger details
SD-XL To Diffusers (fp16) is a tool designed to convert Stable Diffusion XL checkpoints into a format compatible with the Diffusers library, leveraging fp16 precision for optimized performance. This tool simplifies the process of adapting pre-trained models for use in diffusion-based generative tasks while maintaining efficiency and accuracy.
What does SD-XL To Diffusers (fp16) do?
It converts Stable Diffusion XL checkpoints into Diffusers-compatible models with fp16 precision.
Why is fp16 used instead of fp32?
fp16 reduces memory usage and accelerates inference while maintaining sufficient precision for most generative tasks.
Where can I find pre-converted models?
Converted models are typically shared through pull requests in the Diffusers repository or published by the community.
How do I handle errors during conversion?
Check the logs for specific error messages and ensure all dependencies are up-to-date. If issues persist, consider reaching out to the community or reviewing the documentation.
Can I use this tool for other models?
Currently, it is optimized for Stable Diffusion XL checkpoints. Support for other models may be added in future updates.