Instructions to use hchen657Naza/PWM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hchen657Naza/PWM with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hchen657Naza/PWM", 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
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Download PWM_code/RISE_aux/docs/data_preparation.md from hchen657Naza/PWM: direct link, hf CLI and curl.
- Browser
- Download file 650 Bytes
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https://huggingface.co/hchen657Naza/PWM/resolve/main/PWM_code/RISE_aux/docs/data_preparation.md
- Command line
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hf download hf://hchen657Naza/PWM/PWM_code/RISE_aux/docs/data_preparation.md
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curl -L -o data_preparation.md https://huggingface.co/hchen657Naza/PWM/resolve/main/PWM_code/RISE_aux/docs/data_preparation.md
650 Bytes
| # Data Preparation | |
| The training code expects LeRobot-style data. | |
| ## Expected Dataset Layout | |
| ```text | |
| <dataset_name>/ | |
| βββ data/chunk-000/episode_*.parquet | |
| βββ meta/ | |
| β βββ info.json | |
| β βββ episodes.jsonl | |
| β βββ episodes_stats.jsonl | |
| β βββ tasks.jsonl | |
| βββ videos/chunk-000/*.mp4 | |
| ``` | |
| ## Useful Utilities | |
| - ALOHA conversion example: | |
| - `policy_and_value/policy_offline_and_value/examples/aloha_real/convert_to_lerobot.py` | |
| - Lightweight LeRobot tools: | |
| - `policy_and_value/policy_offline_and_value/mini_lerobot/` | |
| - Dynamics-model video resize helper: | |
| - `dynamics/dynamics_model/preprocess.sh` | |