Text Classification
Transformers
Safetensors
modernbert
Generated from Trainer
text-embeddings-inference
Instructions to use harun27/binary_paragraph with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harun27/binary_paragraph with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="harun27/binary_paragraph")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("harun27/binary_paragraph") model = AutoModelForSequenceClassification.from_pretrained("harun27/binary_paragraph", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- config.json +1 -1
- model.safetensors +1 -1
- training_args.bin +1 -1
config.json
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"bos_token_id": 50281,
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"classifier_activation": "gelu",
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"classifier_bias": false,
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"classifier_dropout": 0.
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"classifier_pooling": "mean",
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"decoder_bias": true,
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"bos_token_id": 50281,
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"classifier_activation": "gelu",
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"classifier_dropout": 0.0,
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"classifier_pooling": "mean",
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"cls_token_id": 50281,
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"decoder_bias": true,
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model.safetensors
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training_args.bin
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