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:
- 517971e2a2ac387072db16576277c6c7b8d41a0b57de0b63289f308ffaf30aaa
- Size of remote file:
- 3.25 kB
- SHA256:
- 4cc3313bb54e671510a3bdc6d2ece83701428fae08e2c94c238918f94fe2e79b
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