Instructions to use tiya1012/stress_roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tiya1012/stress_roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tiya1012/stress_roberta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tiya1012/stress_roberta") model = AutoModelForSequenceClassification.from_pretrained("tiya1012/stress_roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from tiya1012/stress_roberta: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/tiya1012/stress_roberta/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://tiya1012/stress_roberta/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tiya1012/stress_roberta/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- dddedbd90a639c2906c203e39a936a841ae5207be85fced705b0300d537e5604
- Size of remote file:
- 499 MB
- SHA256:
- 274411b341d31277a55c305043b8c3af1f2a8ffc66219ac550419aab43cbadea
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