Instructions to use mohsenfayyaz/distilbert-fa-description-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mohsenfayyaz/distilbert-fa-description-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mohsenfayyaz/distilbert-fa-description-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mohsenfayyaz/distilbert-fa-description-classifier") model = AutoModelForSequenceClassification.from_pretrained("mohsenfayyaz/distilbert-fa-description-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 492a0853ce91abd452544f0958b7d957f31f3a7e91a7a7ab4ef9e6f3fc08dc07
- Size of remote file:
- 303 MB
- SHA256:
- 2cbcc75c83bc231cafd789e7624e8a733ec517aad27ff172acfea3f21f6d23b5
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