Instructions to use Srjnnnn/distilbert-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Srjnnnn/distilbert-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Srjnnnn/distilbert-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Srjnnnn/distilbert-sentiment") model = AutoModelForSequenceClassification.from_pretrained("Srjnnnn/distilbert-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 67689e22895ea86023461dfb782be8dd325d5f65ebfc321ac24752052560aa07
- Size of remote file:
- 3.51 kB
- SHA256:
- 07d9117fe1dbb3e95b6bdfa9115f0dd4ce25d6f70baa06a5d6a6123b4547be19
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