Instructions to use FrankCCCCC/cfm-corr-150-ss0.0-ep500-ema-50k-run2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FrankCCCCC/cfm-corr-150-ss0.0-ep500-ema-50k-run2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("FrankCCCCC/cfm-corr-150-ss0.0-ep500-ema-50k-run2", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
File size: 610 Bytes
d3b3957 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | # cfm_corr_150_ss0.0_ep500_ema-50k-run2
This repository contains model artifacts and configuration files from the CFM_CORR_EMA_50k experiment.
## Contents
This folder contains:
- Model checkpoints and weights
- Configuration files (JSON)
- Scheduler and UNet components
- Training results and metadata
- Sample directories (excluding image files)
## Experiment Details
- Experiment: CFM_CORR_EMA_50k
- Folder: cfm_corr_150_ss0.0_ep500_ema-50k-run2
- Images excluded from upload
## Usage
This repository contains the necessary files to reproduce or analyze the model from this specific experimental run.
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