Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Abubakari/finetuned-Sentiment-classfication-ROBERTA-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Abubakari/finetuned-Sentiment-classfication-ROBERTA-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Abubakari/finetuned-Sentiment-classfication-ROBERTA-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Abubakari/finetuned-Sentiment-classfication-ROBERTA-model") model = AutoModelForSequenceClassification.from_pretrained("Abubakari/finetuned-Sentiment-classfication-ROBERTA-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46319d2f8362c6244c89a83460003d22c3576293ebff9e3c7d799896d9d961f4
- Size of remote file:
- 3.84 kB
- SHA256:
- 344a373a8291d06c8b087b1ec8a888e7d63feb2ff9a927ca789f97e6231d4690
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