Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
roberta
stress
classification
glassdoor
Eval Results (legacy)
text-embeddings-inference
Instructions to use dstefa/roberta-base_stress_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dstefa/roberta-base_stress_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dstefa/roberta-base_stress_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dstefa/roberta-base_stress_classification") model = AutoModelForSequenceClassification.from_pretrained("dstefa/roberta-base_stress_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0bc433d8988e14992fd5c3338a7ae2db27f1c1dd6fa91f8c29b488cc8a1d459b
- Size of remote file:
- 19.5 kB
- SHA256:
- 32d28df65598b55a7a86469a032ec58c79c56485c2c6eb4b67dcf076a4c66119
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