Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
sentiment-analysis
text-embeddings-inference
Instructions to use DerivedFunction01/roberta-imdb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DerivedFunction01/roberta-imdb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DerivedFunction01/roberta-imdb")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DerivedFunction01/roberta-imdb") model = AutoModelForSequenceClassification.from_pretrained("DerivedFunction01/roberta-imdb") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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base_model: FacebookAI/roberta-base
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- Transformers 5.0.0
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- Pytorch 2.10.0+cu128
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- Datasets 4.0.0
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- Tokenizers 0.22.2
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base_model: FacebookAI/roberta-base
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tags:
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- generated_from_trainer
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- sentiment-analysis
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metrics:
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- accuracy
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model-index:
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- Transformers 5.0.0
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- Pytorch 2.10.0+cu128
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- Datasets 4.0.0
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- Tokenizers 0.22.2
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