Instructions to use rezaFarsh/binary_persian_sentiment_analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rezaFarsh/binary_persian_sentiment_analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rezaFarsh/binary_persian_sentiment_analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rezaFarsh/binary_persian_sentiment_analysis") model = AutoModelForSequenceClassification.from_pretrained("rezaFarsh/binary_persian_sentiment_analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 74fbbc5e63bfbc403025d2cd0c3c10170dda1a23c3bf386425e1a866c4cfa8e6
- Size of remote file:
- 1.88 GB
- SHA256:
- 04ea1ec1fdcbbbc9b8087ad1f92871cba5637dab3737c01927a7a4f028ecd3f3
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