Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use gArthur98/Roberta-classweight-Sentiment-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gArthur98/Roberta-classweight-Sentiment-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gArthur98/Roberta-classweight-Sentiment-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gArthur98/Roberta-classweight-Sentiment-classifier") model = AutoModelForSequenceClassification.from_pretrained("gArthur98/Roberta-classweight-Sentiment-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4079b2dc28664360fc7650fcdeb7e95474309b40929dde9ce40459aabb7ab102
- Size of remote file:
- 499 MB
- SHA256:
- 4362b60bccdaf5c42bdbd62b222344073260cb36108c4a069abf4ade587bb3e2
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