Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Neha2608/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Neha2608/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Neha2608/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Neha2608/results") model = AutoModelForSequenceClassification.from_pretrained("Neha2608/results") - Notebooks
- Google Colab
- Kaggle
Hurray! Almost finished as training is complete.
Browse files
pytorch_model.bin
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runs/Aug17_00-01-24_fe83b48d5ee2/events.out.tfevents.1660694700.fe83b48d5ee2.77.0
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