Text Classification
Transformers
TensorFlow
English
distilbert
generated_from_keras_callback
text-embeddings-inference
Instructions to use filippo571/pull_request_comments_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use filippo571/pull_request_comments_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="filippo571/pull_request_comments_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("filippo571/pull_request_comments_model") model = AutoModelForSequenceClassification.from_pretrained("filippo571/pull_request_comments_model") - Notebooks
- Google Colab
- Kaggle
Commit ·
0761aca
1
Parent(s): 1ab4df6
Tokenizer of the model
Browse files- tokenizer.json +8 -1
tokenizer.json
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"strategy": "LongestFirst",
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"stride": 0
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"padding":
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"added_tokens": [
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"id": 0,
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"strategy": "LongestFirst",
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"stride": 0
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"padding": {
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"strategy": "BatchLongest",
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"direction": "Right",
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"pad_to_multiple_of": null,
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"pad_id": 0,
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"pad_type_id": 0,
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"pad_token": "[PAD]"
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"added_tokens": [
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"id": 0,
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