Instructions to use horsbug98/Part_1_XLM_Model_E1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use horsbug98/Part_1_XLM_Model_E1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="horsbug98/Part_1_XLM_Model_E1")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("horsbug98/Part_1_XLM_Model_E1") model = AutoModelForQuestionAnswering.from_pretrained("horsbug98/Part_1_XLM_Model_E1") - 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 sha256:68f990b9700e844a9884c462c30c4afbf56d44d504ddd1e64f89d907b6448e67
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size 2991
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