Text Classification
Transformers
PyTorch
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use leobg/deeva-modcat-seqclass-deberta-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leobg/deeva-modcat-seqclass-deberta-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="leobg/deeva-modcat-seqclass-deberta-v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("leobg/deeva-modcat-seqclass-deberta-v1") model = AutoModelForSequenceClassification.from_pretrained("leobg/deeva-modcat-seqclass-deberta-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 16
Browse files- pytorch_model.bin +1 -1
pytorch_model.bin
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