Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Falah/sentiments-dataset-381-classes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Falah/sentiments-dataset-381-classes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Falah/sentiments-dataset-381-classes")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Falah/sentiments-dataset-381-classes") model = AutoModelForSequenceClassification.from_pretrained("Falah/sentiments-dataset-381-classes") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff5ae613bf1260cb6dd36df5603c6957b19f537ee0a20fbf3532e40b00bec937
- Size of remote file:
- 269 MB
- SHA256:
- 1d7bb15e0f0148e9b12a5e8b5674691debd2b0030078395cf9dcbd916849d3da
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