Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Seema09/finetuning-sentiment-model-Test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Seema09/finetuning-sentiment-model-Test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Seema09/finetuning-sentiment-model-Test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Seema09/finetuning-sentiment-model-Test") model = AutoModelForSequenceClassification.from_pretrained("Seema09/finetuning-sentiment-model-Test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe20ad2046a686af336fb1731b8041eae283d45def8f23afdef2f1170b427ec5
- Size of remote file:
- 268 MB
- SHA256:
- f8502d436d31afad3ea76cd5b4e92520eaa4519f398e12b0f4e4a691a37d144d
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