Instructions to use karths/binary_classification_train_usab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_usab with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_usab")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_usab") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_usab", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from karths/binary_classification_train_usab: direct link, hf CLI and curl.
- Browser
- Download file 328 MB
-
https://huggingface.co/karths/binary_classification_train_usab/resolve/main/model.safetensors
- Command line
-
hf download hf://karths/binary_classification_train_usab/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/karths/binary_classification_train_usab/resolve/main/model.safetensors
328 MB
- Xet hash:
- d5f37fcb3a0f4ccd2ddea1a328b25a98e3596e8fa8375c1a231ee45a7e6e7ca9
- Size of remote file:
- 328 MB
- SHA256:
- beadc08a56f100fde4c91910066cb811227f3ed59602afeddc2f31ca16e578af
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