Instructions to use karths/binary_classification_train_automation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_automation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_automation")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_automation") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_automation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-695/rng_state.pth from karths/binary_classification_train_automation: direct link, hf CLI and curl.
- Browser
- Download file 14.2 kB
-
https://huggingface.co/karths/binary_classification_train_automation/resolve/main/checkpoint-695/rng_state.pth
- Command line
-
hf download hf://karths/binary_classification_train_automation/checkpoint-695/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/karths/binary_classification_train_automation/resolve/main/checkpoint-695/rng_state.pth
14.2 kB
- Xet hash:
- 958d9a91a646a6c1fb4d59197734263ade7c4ac190e31bab2f97a444a811065b
- Size of remote file:
- 14.2 kB
- SHA256:
- 3bfc18c7b90ee4da14dfb154c19dea9835dfce97b17d5be2fedec99c35d8da53
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