Instructions to use sms1097/utility_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sms1097/utility_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sms1097/utility_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sms1097/utility_model") model = AutoModelForSequenceClassification.from_pretrained("sms1097/utility_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec0fb63f52b2f2beb5645dded3173940290f774576a9e80e999374f59615243d
- Size of remote file:
- 4.66 kB
- SHA256:
- 8f5827928330466f5d7f7a2461c8529188005190801fe9c6d613b900625ae90d
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