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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 03a2e2f04987d08d5d5cc105b2a2e11a2e41d6c56c92473b6412e93060ef749f
- Size of remote file:
- 14.7 MB
- SHA256:
- 5e825ffb398bd7e888e5350aaaf12dd441d091cdb3fd2e232d8210a8397d4aca
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.