Instructions to use traptrip/rosatom_survey_sentiment_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use traptrip/rosatom_survey_sentiment_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="traptrip/rosatom_survey_sentiment_classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("traptrip/rosatom_survey_sentiment_classifier") model = AutoModelForSequenceClassification.from_pretrained("traptrip/rosatom_survey_sentiment_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from traptrip/rosatom_survey_sentiment_classifier: direct link, hf CLI and curl.
- Browser
- Download file 117 MB
-
https://huggingface.co/traptrip/rosatom_survey_sentiment_classifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://traptrip/rosatom_survey_sentiment_classifier/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/traptrip/rosatom_survey_sentiment_classifier/resolve/main/pytorch_model.bin
117 MB
- Xet hash:
- 6e80707a1c5095c548a5462288fbbb3aaf53edddaa83ffc3a367382c5228e870
- Size of remote file:
- 117 MB
- SHA256:
- 1caae1f8cc01d3fbbdb353beb849ec4ad34c37352f925d288731cd34c4966933
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