Instructions to use minoosh/bert-reg-crossencoder-contrastive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use minoosh/bert-reg-crossencoder-contrastive with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="minoosh/bert-reg-crossencoder-contrastive")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("minoosh/bert-reg-crossencoder-contrastive") model = AutoModelForSequenceClassification.from_pretrained("minoosh/bert-reg-crossencoder-contrastive", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from minoosh/bert-reg-crossencoder-contrastive: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
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https://huggingface.co/minoosh/bert-reg-crossencoder-contrastive/resolve/main/tokenizer.json
- Command line
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hf download hf://minoosh/bert-reg-crossencoder-contrastive/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/minoosh/bert-reg-crossencoder-contrastive/resolve/main/tokenizer.json
712 kB
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