Instructions to use onkarsus13/UniDFlow-A2A with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use onkarsus13/UniDFlow-A2A with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("onkarsus13/UniDFlow-A2A", 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: 863 Bytes
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"batch_size": 2,
"accum_iter": 4,
"epochs": 2,
"warmup_epochs": 0.001,
"lr": 2e-05,
"min_lr": 2e-05,
"wd": 0.1,
"clip_grad": 4.0,
"init_from": "",
"data_config": "",
"cache_ann_on_disk": true,
"length_clustering": true,
"num_workers": 16,
"pin_mem": true,
"seed": 0,
"output_dir": "",
"save_interval": 1,
"save_iteration_interval": 200,
"only_save_trainable": false,
"ckpt_max_keep": 2,
"auto_resume": true,
"resume_path": null,
"model_parallel_size": 1,
"data_parallel": "sdp",
"precision": "bf16",
"grad_precision": "fp32",
"checkpointing": false,
"max_seq_len": 5120,
"mask_image_logits": false,
"dropout": 0.05,
"z_loss_weight": 1e-05,
"model_size": "7B",
"world_size": 48,
"rank": 0,
"gpu": 0,
"local_rank": 0,
"dist_url": "env://",
"distributed": true,
"dist_backend": "nccl"
} |