Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use C-L-V/PsyDefDetect_roberta-base_merged_lr-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use C-L-V/PsyDefDetect_roberta-base_merged_lr-4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="C-L-V/PsyDefDetect_roberta-base_merged_lr-4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("C-L-V/PsyDefDetect_roberta-base_merged_lr-4") model = AutoModelForSequenceClassification.from_pretrained("C-L-V/PsyDefDetect_roberta-base_merged_lr-4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fa268b7aed4ccf01687a7c6f662d2c9353ae147a90e59325946726bddd76aa90
- Size of remote file:
- 5.27 kB
- SHA256:
- 85c210816337d494e49b1e0b09c7b292a7a79da61602f24a0f324a9e7be859aa
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