Instructions to use FrankCCCCC/cfm-corr-800-ss0.0-ep500-ema-50k-run0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FrankCCCCC/cfm-corr-800-ss0.0-ep500-ema-50k-run0 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-800-ss0.0-ep500-ema-50k-run0", 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
Download config.json from FrankCCCCC/cfm-corr-800-ss0.0-ep500-ema-50k-run0: direct link, hf CLI and curl.
- Browser
- Download file 1.38 kB
-
https://huggingface.co/FrankCCCCC/cfm-corr-800-ss0.0-ep500-ema-50k-run0/resolve/main/config.json
- Command line
-
hf download hf://FrankCCCCC/cfm-corr-800-ss0.0-ep500-ema-50k-run0/config.json
-
curl -L -o config.json https://huggingface.co/FrankCCCCC/cfm-corr-800-ss0.0-ep500-ema-50k-run0/resolve/main/config.json
1.38 kB
| { | |
| "save_model_per_ep": 5, | |
| "checkpoint_per_ep": 5, | |
| "ep_model_dir": "epochs", | |
| "output_dir": "fm_cifar10", | |
| "ckpt_dir": "ckpt", | |
| "ckpt_data_file": "data.ckpt", | |
| "is_save_all_model_epochs": false, | |
| "args_key": "args", | |
| "default_key": "default", | |
| "final_key": "final", | |
| "config_file": "config.json", | |
| "optim_name": "adamw", | |
| "shed_name": "poly_decay", | |
| "sched_num_warmup_steps": 45000, | |
| "optim_weight_decay": 0.0, | |
| "optim_beta_1": 0.9, | |
| "optim_beta_2": 0.999, | |
| "optim_epsilon": 1e-08, | |
| "sched_lr_end": 1e-07, | |
| "sched_power": 1.0, | |
| "sched_t_max": 200, | |
| "sched_last_epoch": -1, | |
| "training_result_file": "training_result.json", | |
| "check_finished_file": "finished.json", | |
| "project": "CFM_CORR_EMA_50k", | |
| "name_postfix": "ema-50k-run0", | |
| "saving_strategy": "best_valid_loss", | |
| "optim_lr": 0.0005, | |
| "model_id": "google/ddpm-cifar10-32", | |
| "train_dataset": "cifar10", | |
| "traj_dataset": "data/traj_dataset/TRAJ-DS_PS-DM_DDPM_PSS-1000_SZ-50000", | |
| "batch_size": 256, | |
| "num_epochs": 500, | |
| "num_train_timesteps": 1000, | |
| "predictor_num_inference_steps": 1000, | |
| "corrector_num_inference_steps": 100, | |
| "sigma_min": 0.0, | |
| "sigma_src": 0.0, | |
| "corr_trained_timestep": 800, | |
| "ds_size": 50000, | |
| "seed": 42, | |
| "device": "cuda:0", | |
| "overwrite": false, | |
| "weight_decay": 0.0 | |
| } |