Instructions to use Abhishek4/Cuad_Finetune_roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Abhishek4/Cuad_Finetune_roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Abhishek4/Cuad_Finetune_roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Abhishek4/Cuad_Finetune_roberta") model = AutoModelForTokenClassification.from_pretrained("Abhishek4/Cuad_Finetune_roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 024004646897cefa7fb481b23f0f8aeae84ad98ac1cb2115eef3dfe38fa44afe
- Size of remote file:
- 496 MB
- SHA256:
- a28b32c2124f80cc1298a4bdf47519693bafaac4ac9d0552826516aafecb9b3a
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