Instructions to use CLTL/binary_icf_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLTL/binary_icf_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CLTL/binary_icf_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CLTL/binary_icf_classifier") model = AutoModelForSequenceClassification.from_pretrained("CLTL/binary_icf_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e4868d70901e8828093ab9b5cfa82418f60aad0a9c293d9b83b16a03bd5b7a78
- Size of remote file:
- 504 MB
- SHA256:
- f96cd337763089f3451aec344220c089f94ea2cce4856ef53c0d43a8f5b1afad
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