Instructions to use intanm/mbert-squad2-webis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intanm/mbert-squad2-webis 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="intanm/mbert-squad2-webis")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("intanm/mbert-squad2-webis") model = AutoModelForQuestionAnswering.from_pretrained("intanm/mbert-squad2-webis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update README.md
f12f154
-
update model card README.md
4ed83f2 -
End of training
474c0f0 -
Training in progress, step 2000
1b43a2f -
Training in progress, step 1500
00e6713 -
Training in progress, step 1000
e4d264a -
Training in progress, step 500
1b368fc -
initial commit
f93d7e5