Instructions to use karths/binary_classification_train_people with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_people with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_people")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_people") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_people", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from karths/binary_classification_train_people: direct link, hf CLI and curl.
- Browser
- Download file 328 MB
-
https://huggingface.co/karths/binary_classification_train_people/resolve/main/model.safetensors
- Command line
-
hf download hf://karths/binary_classification_train_people/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/karths/binary_classification_train_people/resolve/main/model.safetensors
328 MB
- Xet hash:
- 3d0a39a9d325f594a0ca915babf0447f303d5392f62d296833f4da679fac47ef
- Size of remote file:
- 328 MB
- SHA256:
- 03abec361d17511829e6c92d917bb55de09a3de9b0878d667346f8d83d3471fa
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