Instructions to use srcocotero/bert-qa-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use srcocotero/bert-qa-en with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="srcocotero/bert-qa-en")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("srcocotero/bert-qa-en") model = AutoModelForQuestionAnswering.from_pretrained("srcocotero/bert-qa-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Add evaluation results on the plain_text config and validation split of squad
Beep boop, I am a bot from Hugging Face's automatic model evaluator 👋!\ Your model has been evaluated on the plain_text config and validation split of the [squad](https://huggingface.co/datasets/squad) dataset by @abrar06, using the predictions stored [here](https://huggingface.co/datasets/autoevaluate/autoeval-eval-squad-plain_text-0a0542-2518877374).\ Accept this pull request to see the results displayed on the [Hub leaderboard](https://huggingface.co/spaces/autoevaluate/leaderboards?dataset=squad).\ Evaluate your model on more datasets [here](https://huggingface.co/spaces/autoevaluate/model-evaluator?dataset=squad).4b93361
-
End of training
ef4523f -
update model card README.md
cf49587 -
Model save
7cf1f71 -
Training in progress, step 500
96ce22c -
initial commit
335f59f