Text Classification
Transformers
PyTorch
Safetensors
Enawené-Nawé
deberta-v2
text-embeddings-inference
Instructions to use labofsahil/mod with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use labofsahil/mod with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="labofsahil/mod")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("labofsahil/mod") model = AutoModelForSequenceClassification.from_pretrained("labofsahil/mod") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a18d063ce61aab7c57bab2077b5b92074a692178654f9bca300d3cd9511a8976
- Size of remote file:
- 1.74 GB
- SHA256:
- 723b68493e28cab1925a0b0c7874d94019ed351dcb9215b07d0dd4f232fe77a9
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