Instructions to use kumar9/word-auto-filled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kumar9/word-auto-filled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kumar9/word-auto-filled")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kumar9/word-auto-filled") model = AutoModelForSequenceClassification.from_pretrained("kumar9/word-auto-filled", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Create config.json
Browse files- config.json +8 -0
config.json
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{
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"_name_or_path": "bert-base-uncased",
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"architectures": [
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"BertForSequenceClassification"
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],
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"model_type": "bert",
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}
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