Instructions to use sms1097/support_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sms1097/support_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sms1097/support_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sms1097/support_model") model = AutoModelForSequenceClassification.from_pretrained("sms1097/support_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 699179bb9544e4e0abc842b011333c3abf861ecd9a8fedfc380aceaa1d11f9df
- Size of remote file:
- 4.66 kB
- SHA256:
- 632955cb16ea6cc959039cbb15af5081ee19e9fa5b4b642e6676ee9c86b14de9
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