Text Classification
Transformers
PyTorch
Enawené-Nawé
roberta
Trained with AutoTrain
text-embeddings-inference
Instructions to use davis901/roberta-frame-CP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davis901/roberta-frame-CP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="davis901/roberta-frame-CP")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("davis901/roberta-frame-CP") model = AutoModelForSequenceClassification.from_pretrained("davis901/roberta-frame-CP") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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oid sha256:8b636eefd8136b5bd6b854cfbdb6934cc6751faa3c6e76243612155ac74337cb
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size 1421499616
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