Instructions to use tdobrxl/Sentiment_analysis_PI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tdobrxl/Sentiment_analysis_PI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tdobrxl/Sentiment_analysis_PI")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tdobrxl/Sentiment_analysis_PI") model = AutoModelForSequenceClassification.from_pretrained("tdobrxl/Sentiment_analysis_PI", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from tdobrxl/Sentiment_analysis_PI: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/tdobrxl/Sentiment_analysis_PI/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://tdobrxl/Sentiment_analysis_PI/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tdobrxl/Sentiment_analysis_PI/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- b6eb50c1d74d9b10d10aae1a3a03d00e0000b1a39f47fc61223c5bd3e8a6e640
- Size of remote file:
- 499 MB
- SHA256:
- 328a9d899df98adc4f79d1afb9f29f8ad404a5df3b8fff062ba99b3c5da1dba4
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