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 training_args.bin from rezaFarsh/binary_persian_sentiment_analysis: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/rezaFarsh/binary_persian_sentiment_analysis/resolve/main/training_args.bin
- Command line
-
hf download hf://rezaFarsh/binary_persian_sentiment_analysis/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/rezaFarsh/binary_persian_sentiment_analysis/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- f7f5b9d370118470d09689eb62ad238008debc6291785dbee32c25c6d7d66068
- Size of remote file:
- 4.6 kB
- SHA256:
- 43ff95d2e9fef78b8dc6e423c1ef43a8b3ed925349cc73da6c0154e2c1c67272
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