Instructions to use Row11n/WAM-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Cosmos
How to use Row11n/WAM-v2 with Cosmos:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
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Download README.md from Row11n/WAM-v2: direct link, hf CLI and curl.
- Browser
- Download file 834 Bytes
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https://huggingface.co/Row11n/WAM-v2/resolve/main/README.md
- Command line
-
hf download hf://Row11n/WAM-v2/README.md
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curl -L -H "Authorization: Bearer $HF_TOKEN" -o README.md https://huggingface.co/Row11n/WAM-v2/resolve/main/README.md
834 Bytes
metadata
library_name: pytorch
tags:
- robotics
- world-action-model
- cosmos
- distributed-checkpoint
WAM v2
This repository contains the latest complete WAM v2 CPT checkpoint based on Cosmos-3 Edge.
Checkpoint
- Training run:
wam-pm32-r50k-256-c128-p9-0826-0518 - Step:
120000 - Repository path:
checkpoints/iter_000120000/ - Format: PyTorch Distributed Checkpoint (DCP)
- Total size: 31,633,628,801 bytes
- File count: 132
- Components:
model,optim,scheduler, andtrainer
This is a resumable training checkpoint, not a standalone Transformers from_pretrained export. Restore it with the DCP loading path in the training code.
Code
Full training code and installation instructions:
- https://github.com/Row11n/WAM-Cosmos3
- Code commit used for migration:
f85124fce30c225b605d224a853f902d9758ed23