Instructions to use amburger66/robometer-4b-lora-robotsmith-task07 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amburger66/robometer-4b-lora-robotsmith-task07 with Transformers:
# Load model directly from transformers import AutoProcessor, RBM processor = AutoProcessor.from_pretrained("amburger66/robometer-4b-lora-robotsmith-task07") model = RBM.from_pretrained("amburger66/robometer-4b-lora-robotsmith-task07") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b2a972deb7f07241536df237b6666f4fc152a8f6dc8d02c86cc9995003d3bd9e
- Size of remote file:
- 5.84 kB
- SHA256:
- a7c75ad6cf635d70d5cdadb8987b8c485cb824ef2c9763290ac9e8068a9337fd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.