Instructions to use Mustafayaz/department-classifier-ayaz with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mustafayaz/department-classifier-ayaz with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mustafayaz/department-classifier-ayaz")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mustafayaz/department-classifier-ayaz") model = AutoModelForSequenceClassification.from_pretrained("Mustafayaz/department-classifier-ayaz", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a740a324797649682aa2827704fde53be994f6331474e51c04cc31fa1a8d3bc
- Size of remote file:
- 268 MB
- SHA256:
- 45723b7b13792e73c781ac175673862c0bb3b03d8f9d99dd1f42a05857ee1f36
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