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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("leblanciii/trident-peril-classifier") model = AutoModelForMaskedLM.from_pretrained("leblanciii/trident-peril-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Upload multi-task peril/severity/category classifier
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Upload multi-task peril/severity/category classifier
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Upload 6-head multi-task classifier (peril+severity+category+fire_sub+relevance+actionability)
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Upload 4-head multi-task classifier (peril+severity+category+fire_sub)
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Add id2label/label2id mappings for readable predictions
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Add model card with pipeline_tag for inference API
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Upload RoBERTa peril classifier
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initial commit
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