Instructions to use Debashmita/Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Debashmita/Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Debashmita/Model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Debashmita/Model") model = AutoModelForSequenceClassification.from_pretrained("Debashmita/Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ae67b57726e726855fa54a13bb199976a81f4ff76a255f81d59537c304eb0e31
- Size of remote file:
- 442 MB
- SHA256:
- 0650479f34b6e744e0707afcf5f8d36ab1522e34bb6eb8ca2a0f94fe5717257c
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