Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use peringe/finetuning-sentiment-model-3000-samples-pi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peringe/finetuning-sentiment-model-3000-samples-pi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="peringe/finetuning-sentiment-model-3000-samples-pi")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("peringe/finetuning-sentiment-model-3000-samples-pi") model = AutoModelForSequenceClassification.from_pretrained("peringe/finetuning-sentiment-model-3000-samples-pi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Ctrl+K