Instructions to use alex019/email_sentiment_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alex019/email_sentiment_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="alex019/email_sentiment_classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("alex019/email_sentiment_classifier") model = AutoModelForSequenceClassification.from_pretrained("alex019/email_sentiment_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from alex019/email_sentiment_classifier: direct link, hf CLI and curl.
- Browser
- Download file 329 MB
-
https://huggingface.co/alex019/email_sentiment_classifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://alex019/email_sentiment_classifier/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/alex019/email_sentiment_classifier/resolve/main/pytorch_model.bin
329 MB
- Xet hash:
- 414c7873e1f2eafaae67f76835a7fd5bae4b38f123008b1dc11851a51c754b22
- Size of remote file:
- 329 MB
- SHA256:
- 11bd2cd43386aa87f0c0efacec4032d1c877cd2b8f3315f0f558e14f694a4501
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