Text Classification
Transformers
PyTorch
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use dipteshkanojia/hing-roberta-NCM-run-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dipteshkanojia/hing-roberta-NCM-run-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dipteshkanojia/hing-roberta-NCM-run-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dipteshkanojia/hing-roberta-NCM-run-2") model = AutoModelForSequenceClassification.from_pretrained("dipteshkanojia/hing-roberta-NCM-run-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a2d8bf4cc1278913488ff86840b1c8bf8e0e9b155944c02e9536d7182c920f3d
- Size of remote file:
- 1.11 GB
- SHA256:
- 7ecae0f97681ea36f9f016edffe5ee4d2b37d993025f4d35eb1f68b51a83231c
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