Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use gArthur98/Roberta-Sentiment-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gArthur98/Roberta-Sentiment-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gArthur98/Roberta-Sentiment-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gArthur98/Roberta-Sentiment-classifier") model = AutoModelForSequenceClassification.from_pretrained("gArthur98/Roberta-Sentiment-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5160200f8d067c52a7bbee8c5722de87879a376c7519f71a08177d567e12335b
- Size of remote file:
- 499 MB
- SHA256:
- 21d4249cf00e4efff23148052e1b83df11ffaf397bc0d06d196fadfcacb80981
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