Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use sumitp76/v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sumitp76/v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sumitp76/v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sumitp76/v1") model = AutoModelForSequenceClassification.from_pretrained("sumitp76/v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9e99e78c00964f09b3ee7556d32af4b8171043bb14c99bace5ab0bcf9c1052af
- Size of remote file:
- 5.2 kB
- SHA256:
- 4c382a7e838a672e67b47ed58e030b3947f3a19df7dc8d8332114181f83fd0da
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