Instructions to use NEUDM/PICA-V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NEUDM/PICA-V1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="NEUDM/PICA-V1", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("NEUDM/PICA-V1", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- da79942457656b71612146b9ae71a53d87c837b074d3d35df60f0c70f8b71043
- Size of remote file:
- 7.34 MB
- SHA256:
- 3a61ebe570601a484132f73b4fd3cb333e87fa29ef2812e5953b2524e705fe0d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.