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
- Xet hash:
- 514b08f446552b9b578d49c540892387f171bf099f8d8adc1df56cbadeff8a39
- Size of remote file:
- 499 MB
- SHA256:
- ce15292532e7dc8befdad63477d0d6c0af989685548b23f007ad69560a0c7b7c
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