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:
- f8de7c05061ab9f453a8364a06de1387a75590b501bb99f9bbb49947907f8e35
- Size of remote file:
- 16.1 kB
- SHA256:
- e459c4eab7a5616d61326b2f208ecb801eddc18219e92410be7c3ef1150b9cf8
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