Text Classification
Transformers
PyTorch
Safetensors
roberta
fill-mask
multi-label-classification
builders-risk
text-embeddings-inference
Instructions to use leblanciii/trident-peril-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leblanciii/trident-peril-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="leblanciii/trident-peril-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("leblanciii/trident-peril-classifier") model = AutoModelForMaskedLM.from_pretrained("leblanciii/trident-peril-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1ffc8c8dc6dde2e710d9dab6297a05cfee5c2492afd206a8ce1f2fc077d4d58b
- Size of remote file:
- 5.2 kB
- SHA256:
- c04b2e6d3ea941219d1833192750daa8e4ecbef8ca6c5a6a21667ad97ef99b3d
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