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
| { | |
| "n_samples": 2000, | |
| "class_proportions": { | |
| "negative": 0.494, | |
| "positive": 0.506 | |
| }, | |
| "confidence_mean": 0.9148861765861511, | |
| "confidence_std": 0.1137993112206459, | |
| "confidence_histogram": { | |
| "bins": [ | |
| 0.0, | |
| 0.1, | |
| 0.2, | |
| 0.30000000000000004, | |
| 0.4, | |
| 0.5, | |
| 0.6000000000000001, | |
| 0.7000000000000001, | |
| 0.8, | |
| 0.9, | |
| 1.0 | |
| ], | |
| "counts": [ | |
| 0, | |
| 0, | |
| 0, | |
| 0, | |
| 0, | |
| 80, | |
| 87, | |
| 108, | |
| 192, | |
| 1533 | |
| ] | |
| }, | |
| "prediction_histogram": { | |
| "neg_bins": [ | |
| 0.0, | |
| 0.1, | |
| 0.2, | |
| 0.30000000000000004, | |
| 0.4, | |
| 0.5, | |
| 0.6000000000000001, | |
| 0.7000000000000001, | |
| 0.8, | |
| 0.9, | |
| 1.0 | |
| ], | |
| "neg_counts": [ | |
| 771, | |
| 100, | |
| 55, | |
| 44, | |
| 42, | |
| 38, | |
| 43, | |
| 53, | |
| 92, | |
| 762 | |
| ], | |
| "pos_bins": [ | |
| 0.0, | |
| 0.1, | |
| 0.2, | |
| 0.30000000000000004, | |
| 0.4, | |
| 0.5, | |
| 0.6000000000000001, | |
| 0.7000000000000001, | |
| 0.8, | |
| 0.9, | |
| 1.0 | |
| ], | |
| "pos_counts": [ | |
| 762, | |
| 92, | |
| 53, | |
| 43, | |
| 38, | |
| 42, | |
| 44, | |
| 55, | |
| 100, | |
| 771 | |
| ] | |
| } | |
| } |