Instructions to use distilbert/distilbert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use distilbert/distilbert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="distilbert/distilbert-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("distilbert/distilbert-base-uncased") model = AutoModelForMaskedLM.from_pretrained("distilbert/distilbert-base-uncased") - Inference
- Notebooks
- Google Colab
- Kaggle
Changed distillation URL
#8
by RatnaKumar - opened
README.md
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@@ -187,7 +187,7 @@ The details of the masking procedure for each sentence are the following:
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### Pretraining
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The model was trained on 8 16 GB V100 for 90 hours. See the
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[training code](https://github.com/huggingface/transformers/tree/
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details.
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## Evaluation results
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### Pretraining
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The model was trained on 8 16 GB V100 for 90 hours. See the
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[training code](https://github.com/huggingface/transformers/tree/main/examples/research_projects/distillation) for all hyperparameters
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details.
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## Evaluation results
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