Instructions to use HARSHU550/Bert_IF_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HARSHU550/Bert_IF_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HARSHU550/Bert_IF_Classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HARSHU550/Bert_IF_Classifier") model = AutoModelForSequenceClassification.from_pretrained("HARSHU550/Bert_IF_Classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download .gitattributes from HARSHU550/Bert_IF_Classifier: direct link, hf CLI and curl.
- Browser
- Download file 400 Bytes
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https://huggingface.co/HARSHU550/Bert_IF_Classifier/resolve/main/.gitattributes
- Command line
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hf download hf://HARSHU550/Bert_IF_Classifier/.gitattributes
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curl -L -o .gitattributes https://huggingface.co/HARSHU550/Bert_IF_Classifier/resolve/main/.gitattributes
400 Bytes
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