Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use mnavas/roberta-finetuned-WebClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mnavas/roberta-finetuned-WebClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mnavas/roberta-finetuned-WebClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mnavas/roberta-finetuned-WebClassification") model = AutoModelForSequenceClassification.from_pretrained("mnavas/roberta-finetuned-WebClassification") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
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by librarian-bot - opened
README.md
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model-index:
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- name: roberta-finetuned-WebClassification
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results: []
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pipeline_tag: text-classification
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- precision
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pipeline_tag: text-classification
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base_model: xlm-roberta-base
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model-index:
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- name: roberta-finetuned-WebClassification
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results: []
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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