Instructions to use mertas7/medroberta-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mertas7/medroberta-binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mertas7/medroberta-binary")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mertas7/medroberta-binary") model = AutoModelForSequenceClassification.from_pretrained("mertas7/medroberta-binary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from mertas7/medroberta-binary: direct link, hf CLI and curl.
- Browser
- Download file 28 Bytes
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https://huggingface.co/mertas7/medroberta-binary/resolve/main/README.md
- Command line
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hf download hf://mertas7/medroberta-binary/README.md
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curl -L -o README.md https://huggingface.co/mertas7/medroberta-binary/resolve/main/README.md
28 Bytes
metadata
license: unknown