Fill-Mask
Transformers
PyTorch
caduceus
biology
genomics
dna
oryza-sativa
rice
variant-effect-prediction
masked-language-modeling
mamba
custom_code
Instructions to use xxl0001/COD-PlantCAD-Rice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xxl0001/COD-PlantCAD-Rice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="xxl0001/COD-PlantCAD-Rice", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("xxl0001/COD-PlantCAD-Rice", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78b6c68788885a7052e8b924ae60de24fdd353f6b31500c7d45b00ecdf33d9f4
- Size of remote file:
- 449 MB
- SHA256:
- 4e2a8d6f3c1eae007e0829ad8021c5807f44042d097f5d611799432fa6352c5c
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