Instructions to use horsbug98/Part_1_mBERT_Model_E2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use horsbug98/Part_1_mBERT_Model_E2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="horsbug98/Part_1_mBERT_Model_E2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("horsbug98/Part_1_mBERT_Model_E2") model = AutoModelForQuestionAnswering.from_pretrained("horsbug98/Part_1_mBERT_Model_E2") - Notebooks
- Google Colab
- Kaggle
Upload training_args.bin with git-lfs
Browse files- training_args.bin +3 -0
training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:1ed516de5cfe3a9a56e491dfbe1b1fd27c30fd3f91922ca5f4d6b85b1edef1f5
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size 3055
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