Instructions to use BroLaurens/finer-distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BroLaurens/finer-distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="BroLaurens/finer-distilbert")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("BroLaurens/finer-distilbert") model = AutoModelForTokenClassification.from_pretrained("BroLaurens/finer-distilbert") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -62,6 +62,7 @@ predicted_labels = [[int2str[x] for x in t] for t in predictions.tolist()]
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The model was trained using the following hyperparameters:
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base_model: distilbert/distilbert-base-uncased
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learning_rate: 2e-5
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batch_size: 32
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adam_beta1: 0.9
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adam_beta2: 0.999
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adam_epsilon: 1e-08
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loss_function: cross entropy loss
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The model was trained using the following hyperparameters:
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```
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base_model: distilbert/distilbert-base-uncased
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learning_rate: 2e-5
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batch_size: 32
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adam_beta1: 0.9
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adam_beta2: 0.999
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adam_epsilon: 1e-08
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loss_function: cross entropy loss
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```
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