Instructions to use karths/binary_classification_train_requirement with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_requirement with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_requirement")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_requirement") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_requirement", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download reduced_main_data.csv from karths/binary_classification_train_requirement: direct link, hf CLI and curl.
- Browser
- Download file 66.6 MB
-
https://huggingface.co/karths/binary_classification_train_requirement/resolve/main/reduced_main_data.csv
- Command line
-
hf download hf://karths/binary_classification_train_requirement/reduced_main_data.csv
-
curl -L -o reduced_main_data.csv https://huggingface.co/karths/binary_classification_train_requirement/resolve/main/reduced_main_data.csv
66.6 MB
- Xet hash:
- 49824c79a6ea0cec8ac740f58b421b2dac1bff70c5c69ff5f7dd0cbce5d2b5cc
- Size of remote file:
- 66.6 MB
- SHA256:
- 2524e9883e79fbb5a0d8df8b8ae42bc8bcec231b87b4ac0ed87adfad6574c84b
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