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
Download training_args.bin from mohsenfayyaz/distilbert-fa-description-classifier: direct link, hf CLI and curl.
- Browser
- Download file 2.42 kB
-
https://huggingface.co/mohsenfayyaz/distilbert-fa-description-classifier/resolve/main/training_args.bin
- Command line
-
hf download hf://mohsenfayyaz/distilbert-fa-description-classifier/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/mohsenfayyaz/distilbert-fa-description-classifier/resolve/main/training_args.bin
2.42 kB
- Xet hash:
- e9385c3ef28a0f65a6197c08ab91074f55b8d3bf65388355b62f844b038e09c6
- Size of remote file:
- 2.42 kB
- SHA256:
- 484003321750316637c575a9bf56937c1c323ecd4a7a753102cd7555a2d44b25
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