Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Carmesix/Sentiment_Analysis_25000sample with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Carmesix/Sentiment_Analysis_25000sample with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Carmesix/Sentiment_Analysis_25000sample")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Carmesix/Sentiment_Analysis_25000sample") model = AutoModelForSequenceClassification.from_pretrained("Carmesix/Sentiment_Analysis_25000sample", device_map="auto") - Notebooks
- Google Colab
- Kaggle