Text Classification
Transformers
PyTorch
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use dipteshkanojia/hing-roberta-CM-run-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dipteshkanojia/hing-roberta-CM-run-4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dipteshkanojia/hing-roberta-CM-run-4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dipteshkanojia/hing-roberta-CM-run-4") model = AutoModelForSequenceClassification.from_pretrained("dipteshkanojia/hing-roberta-CM-run-4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
5fa2430
1
Parent(s): 4ddf5fe
Librarian Bot: Add base_model information to model (#1)
Browse files- Librarian Bot: Add base_model information to model (d942346a84f3d954217133c3c74f9ed9946a49d0)
Co-authored-by: Librarian Bot (Bot) <librarian-bot@users.noreply.huggingface.co>
README.md
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- precision
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- recall
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- f1
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model-index:
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- name: hing-roberta-CM-run-4
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results: []
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- precision
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- recall
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- f1
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base_model: l3cube-pune/hing-roberta
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model-index:
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- name: hing-roberta-CM-run-4
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results: []
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