Instructions to use peter2000/roberta-finetuned-qa-policy_long with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peter2000/roberta-finetuned-qa-policy_long with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="peter2000/roberta-finetuned-qa-policy_long")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("peter2000/roberta-finetuned-qa-policy_long") model = AutoModelForQuestionAnswering.from_pretrained("peter2000/roberta-finetuned-qa-policy_long") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1cb7575d1a2666451a5c73d858b2f12561a0bf104e2c4b783291f82b1d7f988e
- Size of remote file:
- 4.6 kB
- SHA256:
- 3ee81e795c67027deef0e21e08eec99d9450955d32f2f7515918c8f8487d589e
路
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