Instructions to use m3hrdadfi/zabanshenas-roberta-base-mix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m3hrdadfi/zabanshenas-roberta-base-mix with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="m3hrdadfi/zabanshenas-roberta-base-mix")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("m3hrdadfi/zabanshenas-roberta-base-mix") model = AutoModelForSequenceClassification.from_pretrained("m3hrdadfi/zabanshenas-roberta-base-mix") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b28f0b93f4b467d6ed27432de71cd776cdb52f9272c2644332856396c004949
- Size of remote file:
- 443 MB
- SHA256:
- 8863bf86a75da23bd15abd55fd68a0d6e2a8a70851389f96e13580dc356301cd
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