Instructions to use kuleshov-group/PlantCaduceus_l28 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kuleshov-group/PlantCaduceus_l28 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="kuleshov-group/PlantCaduceus_l28", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("kuleshov-group/PlantCaduceus_l28", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4b9d628561c0e8c0c18212c9b4a8d1ec40d67cc5ea8d4bb9c47d577333dd613f
- Size of remote file:
- 449 MB
- SHA256:
- 9b347f14ee41ef9888357e263eff9a8afbeb9bad60205e9e07ea6df2dbd52cc9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.