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:
- cea9accbe80a6ea62aa647cb92b764a09edd5476f08b7b8bc32500c01e5a6c1f
- Size of remote file:
- 3.64 kB
- SHA256:
- 06e3904634e0a7b096d8eb4392b1f0a5c399138d283598073ce811dca6cf7adb
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