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 reduced_main_data.csv from karths/binary_classification_train_usab: direct link, hf CLI and curl.
- Browser
- Download file 129 MB
-
https://huggingface.co/karths/binary_classification_train_usab/resolve/bf73d26480d615feafcb400aeacdb31d09bb2888/reduced_main_data.csv
- Command line
-
hf download hf://karths/binary_classification_train_usab@bf73d26480d615feafcb400aeacdb31d09bb2888/reduced_main_data.csv
-
curl -L -o reduced_main_data.csv https://huggingface.co/karths/binary_classification_train_usab/resolve/bf73d26480d615feafcb400aeacdb31d09bb2888/reduced_main_data.csv
129 MB
- Xet hash:
- e9cb9ee2668ea0c01c5ec94ac1aecf98c569ea97203c32fb26920d9e4e6b4994
- Size of remote file:
- 129 MB
- SHA256:
- 7a0aa8468dc3b829458b19a4d2b922757d25a8b949c08163a991a9bcd364283c
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