Instructions to use horsbug98/Part_2_mBERT_Model_E1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use horsbug98/Part_2_mBERT_Model_E1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="horsbug98/Part_2_mBERT_Model_E1")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("horsbug98/Part_2_mBERT_Model_E1") model = AutoModelForQuestionAnswering.from_pretrained("horsbug98/Part_2_mBERT_Model_E1") - Notebooks
- Google Colab
- Kaggle
Upload train_results.json
Browse files- train_results.json +8 -0
train_results.json
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{
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"epoch": 1.0,
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"train_loss": 1.4328513269978806,
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"train_runtime": 588.3802,
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"train_samples": 14238,
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"train_samples_per_second": 24.199,
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"train_steps_per_second": 2.017
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}
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