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:
- 85bc97ed900fa00d4fbadaf03157ea31e47eae76d488a1ed469c2ebb033bce15
- Size of remote file:
- 3.96 kB
- SHA256:
- 69a8c47c6ba9ba43afafba17a663425fc486a4bce6aa8dca0261ebecd0c2196b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.