Instructions to use karths/binary_classification_train_architecture with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_architecture with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_architecture")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_architecture") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_architecture", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download top_repo_data.csv from karths/binary_classification_train_architecture: direct link, hf CLI and curl.
- Browser
- Download file 2.21 MB
-
https://huggingface.co/karths/binary_classification_train_architecture/resolve/main/top_repo_data.csv
- Command line
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hf download hf://karths/binary_classification_train_architecture/top_repo_data.csv
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curl -L -o top_repo_data.csv https://huggingface.co/karths/binary_classification_train_architecture/resolve/main/top_repo_data.csv
2.21 MB
File too large to display, you can check the raw version instead.