Text Classification
Transformers
Safetensors
distilbert
sentiment
ml-observability
text-embeddings-inference
Instructions to use karaboLLM/sentiment-distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karaboLLM/sentiment-distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karaboLLM/sentiment-distilbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karaboLLM/sentiment-distilbert") model = AutoModelForSequenceClassification.from_pretrained("karaboLLM/sentiment-distilbert") - Notebooks
- Google Colab
- Kaggle
Sentiment Classifier (DistilBERT)
Fine-tuned on IMDB for the ML Observability Platform.
Accuracy: 0.8984
F1 Score: 0.8999
Part of the ml-observability-platform MLOps pipeline.
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