Instructions to use Zahra99/base-article-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Zahra99/base-article-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Zahra99/base-article-1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Zahra99/base-article-1") model = AutoModelForSequenceClassification.from_pretrained("Zahra99/base-article-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 17c8a8a449b143d7d834b72096716912bba3e86cec3ef3af7381f483a7576a30
- Size of remote file:
- 438 MB
- SHA256:
- 527d6be1e16b2f7c4854a9b66d85c9a18e9f7a4cc75af98ce103253226eeb638
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