Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use gArthur98/Finetuned-Roberta-Base-Sentiment-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gArthur98/Finetuned-Roberta-Base-Sentiment-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gArthur98/Finetuned-Roberta-Base-Sentiment-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gArthur98/Finetuned-Roberta-Base-Sentiment-classifier") model = AutoModelForSequenceClassification.from_pretrained("gArthur98/Finetuned-Roberta-Base-Sentiment-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f714d1f045809eb9c3a892497e540e73d51cfac92b3e44cca3eedf12a17cce6d
- Size of remote file:
- 4.03 kB
- SHA256:
- bafe6857a8021488f0d6ab922d64c817942173b3f8c930e596cd1803ed587ff0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.