Instructions to use aabyaneh/fasterwam with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use aabyaneh/fasterwam with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("aabyaneh/fasterwam", 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 checkpoint_layout.json from aabyaneh/fasterwam: direct link, hf CLI and curl.
- Browser
- Download file 484 Bytes
-
https://huggingface.co/aabyaneh/fasterwam/resolve/main/checkpoint_layout.json
- Command line
-
hf download hf://aabyaneh/fasterwam/checkpoint_layout.json
-
curl -L -o checkpoint_layout.json https://huggingface.co/aabyaneh/fasterwam/resolve/main/checkpoint_layout.json
484 Bytes
| { | |
| "model_aliases": { | |
| "flashwam": "fasterwam", | |
| "lingbotva": "lingbot-va", | |
| "pi05": "pi0.5" | |
| }, | |
| "models": [ | |
| "fastwam", | |
| "fasterwam", | |
| "lingbot-va", | |
| "pi0.5" | |
| ], | |
| "repo_type": "model", | |
| "run_path": "<task|joint>/<model>/<run_id>/", | |
| "schema_version": 2, | |
| "tasks": [ | |
| "fruit_pick", | |
| "dish_utensil", | |
| "place_cube", | |
| "push_t" | |
| ], | |
| "top_level_folders": [ | |
| "fruit_pick", | |
| "dish_utensil", | |
| "place_cube", | |
| "push_t", | |
| "joint" | |
| ] | |
| } | |