Instructions to use Adapting/comfort_congratulations_neutral-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Adapting/comfort_congratulations_neutral-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Adapting/comfort_congratulations_neutral-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Adapting/comfort_congratulations_neutral-classifier") model = AutoModelForSequenceClassification.from_pretrained("Adapting/comfort_congratulations_neutral-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8b8843ce8fb4ee754beaa34f8d70dab1cfd756d59ab6ba5a35f1daa18e75dd77
- Size of remote file:
- 268 MB
- SHA256:
- dda96a9ad5126ccab1f66f3c50d32ee05d62392820a779a6fd94734e621422ea
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