Instructions to use SuchithTissera/text_analytics_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SuchithTissera/text_analytics_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SuchithTissera/text_analytics_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SuchithTissera/text_analytics_model") model = AutoModelForSequenceClassification.from_pretrained("SuchithTissera/text_analytics_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload DistilBertForSequenceClassification
Browse files- config.json +0 -1
- model.safetensors +1 -1
config.json
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"n_heads": 12,
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"n_layers": 6,
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"pad_token_id": 0,
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"problem_type": "single_label_classification",
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"qa_dropout": 0.1,
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"seq_classif_dropout": 0.2,
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"sinusoidal_pos_embds": false,
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"n_heads": 12,
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"n_layers": 6,
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"pad_token_id": 0,
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"qa_dropout": 0.1,
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"seq_classif_dropout": 0.2,
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"sinusoidal_pos_embds": false,
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 267841796
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