Instructions to use Ola172/article_classification_modelv1.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ola172/article_classification_modelv1.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ola172/article_classification_modelv1.1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ola172/article_classification_modelv1.1") model = AutoModelForSequenceClassification.from_pretrained("Ola172/article_classification_modelv1.1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Ola172/article_classification_modelv1.1: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
-
https://huggingface.co/Ola172/article_classification_modelv1.1/resolve/main/training_args.bin
- Command line
-
hf download hf://Ola172/article_classification_modelv1.1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Ola172/article_classification_modelv1.1/resolve/main/training_args.bin
5.05 kB
- Xet hash:
- f873a4ca33ec41835c446bb14f9bd165dafff0ba8b99c2a2be767b75d7f13c72
- Size of remote file:
- 5.05 kB
- SHA256:
- b24039348e4b00ad7cdc3a369c827b17bdb70a931a3f7845fcf8e9d90d68e548
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