|
Download task_7/README.md from Recharge23/FastWAM-single: direct link, hf CLI and curl.
- Browser
- Download file 869 Bytes
-
https://huggingface.co/Recharge23/FastWAM-single/resolve/main/task_7/README.md
- Command line
-
hf download hf://Recharge23/FastWAM-single/task_7/README.md
-
curl -L -o README.md https://huggingface.co/Recharge23/FastWAM-single/resolve/main/task_7/README.md
869 Bytes
| # Fast-WAM Task 7 | |
| Independent GELLO specialist initialized from the pinned Fast-WAM Base LIBERO checkpoint. This is a LoRA adapter plus newly trained pose10 input/output projections, not a standalone base model. | |
| Use this folder with the repository's `inference/serve_fastwam.py`, original base and VAE assets, this folder's normalization and exact `prompt.txt`. Input is the current external RGB image and measured base-frame flange pose10. Output is 32 absolute next-achieved flange pose10 targets, with commanded aperture, at 15 Hz target spacing. The server predicts actions without generating future video. | |
| `INFERENCE_REPORT.json` contains the fixed forty held-out-window diagnostics and the final-weight portable/native/HTTP comparison. These checks do not establish physical task success. See the repository's `INFERENCE.md` for installation and client usage. | |