Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use heyal/finetuning-sentiment-model-5000-samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use heyal/finetuning-sentiment-model-5000-samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="heyal/finetuning-sentiment-model-5000-samples")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("heyal/finetuning-sentiment-model-5000-samples") model = AutoModelForSequenceClassification.from_pretrained("heyal/finetuning-sentiment-model-5000-samples") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cde2a8e9feb1ac9d336945ed9b11b635788241bd6cffb9c02ebe000249f2d0a5
- Size of remote file:
- 268 MB
- SHA256:
- e7a95b94336f767edb7190691cf4855564a89da059d8987f078e50a2c0d1ef50
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