Instructions to use Goutham-Vignesh/ContributionSentClassification-scibert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Goutham-Vignesh/ContributionSentClassification-scibert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Goutham-Vignesh/ContributionSentClassification-scibert")# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("Goutham-Vignesh/ContributionSentClassification-scibert", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): fdc913e
Update config.json
Browse files- config.json +1 -1
config.json
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "scibert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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