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")# pip install -U transformers accelerate # 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
Download tokenizer.json from rezaFarsh/binary_persian_sentiment_analysis: direct link, hf CLI and curl.
- Browser
- Download file 13.6 MB
-
https://huggingface.co/rezaFarsh/binary_persian_sentiment_analysis/resolve/main/tokenizer.json
- Command line
-
hf download hf://rezaFarsh/binary_persian_sentiment_analysis/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/rezaFarsh/binary_persian_sentiment_analysis/resolve/main/tokenizer.json
13.6 MB
- Xet hash:
- 6c1494e1ec3ec6150d8a9612a1088352cb8e2505c8d9625a966414d0cc8f983a
- Size of remote file:
- 13.6 MB
- SHA256:
- 0875848db9ea9ea157b382c90b986f2a807e136d3f442e6dd8cdf58b68d0d452
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