Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use daniel780/amazon_sentiment_sample_of_1900_with_summary_larger_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use daniel780/amazon_sentiment_sample_of_1900_with_summary_larger_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="daniel780/amazon_sentiment_sample_of_1900_with_summary_larger_test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("daniel780/amazon_sentiment_sample_of_1900_with_summary_larger_test") model = AutoModelForSequenceClassification.from_pretrained("daniel780/amazon_sentiment_sample_of_1900_with_summary_larger_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle