Instructions to use karths/binary_classification_train_code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_code with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_code")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_code") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_code", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from karths/binary_classification_train_code: direct link, hf CLI and curl.
- Browser
- Download file 328 MB
-
https://huggingface.co/karths/binary_classification_train_code/resolve/main/model.safetensors
- Command line
-
hf download hf://karths/binary_classification_train_code/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/karths/binary_classification_train_code/resolve/main/model.safetensors
328 MB
- Xet hash:
- 390699063e84a3fedf762e38f89f88e0937008798ffab896a73f5771c28f4db1
- Size of remote file:
- 328 MB
- SHA256:
- ddf8cae4165bf8c4ce39f9a029b7910466c5a2651b3a41a86f29e7176e98ca7e
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