Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use gArthur98/Greg-Sentiment-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gArthur98/Greg-Sentiment-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gArthur98/Greg-Sentiment-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gArthur98/Greg-Sentiment-classifier") model = AutoModelForSequenceClassification.from_pretrained("gArthur98/Greg-Sentiment-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f7cfbc737609ae5d59a79054f8d481980e8333dcb02b621267b1d40b55f1756a
- Size of remote file:
- 3.96 kB
- SHA256:
- d5146e6e9359aa416fa0699108110b0a3c3d5ffc7fe949c585a01cf2f879f576
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