Instructions to use Shruthikaa/muril_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shruthikaa/muril_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Shruthikaa/muril_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Shruthikaa/muril_classification") model = AutoModelForSequenceClassification.from_pretrained("Shruthikaa/muril_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d93449366173837ec9820a0277ae8c399a97be2b2b999e00d3f74417674d958f
- Size of remote file:
- 950 MB
- SHA256:
- 55380cc8e990cd2a9d74f607812afedb58a4ce78f8fa69c2b02733b10068e495
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