Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use JonCard/ctc_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JonCard/ctc_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JonCard/ctc_classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JonCard/ctc_classifier") model = AutoModelForSequenceClassification.from_pretrained("JonCard/ctc_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from JonCard/ctc_classifier: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/JonCard/ctc_classifier/resolve/main/model.safetensors
- Command line
-
hf download hf://JonCard/ctc_classifier/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/JonCard/ctc_classifier/resolve/main/model.safetensors
268 MB
- Xet hash:
- d45bf7f659f6595816a131368742755e086c6fceba46e668ebd736f1c47f58a2
- Size of remote file:
- 268 MB
- SHA256:
- d601105d38c792117db9425f55236eff62fe15b875139fa9cb796eadcffc5bfc
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