Instructions to use The-Adnan-Syed/Stress_Classifier_BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use The-Adnan-Syed/Stress_Classifier_BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="The-Adnan-Syed/Stress_Classifier_BERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("The-Adnan-Syed/Stress_Classifier_BERT") model = AutoModelForSequenceClassification.from_pretrained("The-Adnan-Syed/Stress_Classifier_BERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download label_encoder.joblib from The-Adnan-Syed/Stress_Classifier_BERT: direct link, hf CLI and curl.
- Browser
- Download file 598 Bytes
-
https://huggingface.co/The-Adnan-Syed/Stress_Classifier_BERT/resolve/main/label_encoder.joblib
- Command line
-
hf download hf://The-Adnan-Syed/Stress_Classifier_BERT/label_encoder.joblib
-
curl -L -o label_encoder.joblib https://huggingface.co/The-Adnan-Syed/Stress_Classifier_BERT/resolve/main/label_encoder.joblib
598 Bytes
- Xet hash:
- 61265757ec8c2875fb9846d3eedb1163124daeea9d4e7ca4234acb10113251d5
- Size of remote file:
- 598 Bytes
- SHA256:
- 0391e47895e594174e83bb24b80bc11e60765e764f788ac963ff1115f9441455
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