Instructions to use NCHS/SANDS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NCHS/SANDS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NCHS/SANDS")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NCHS/SANDS") model = AutoModelForSequenceClassification.from_pretrained("NCHS/SANDS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README from local repo
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README.md
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@@ -162,6 +162,7 @@ The model was fine-tuned on 3,000 labeled open-ended responses from [RANDS durin
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author={Kristen Cibelli Hibben, Zachary Smith, Ben Rogers, Valerie Ryan, Paul Scanlon, Kristen Miller, Travis Hoppe},
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year={2023},
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url={https://huggingface.co/NCHS/SANDS},
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}
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```
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author={Kristen Cibelli Hibben, Zachary Smith, Ben Rogers, Valerie Ryan, Paul Scanlon, Kristen Miller, Travis Hoppe},
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year={2023},
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url={https://huggingface.co/NCHS/SANDS},
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doi={ 10.57967/hf/0414 }
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}
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```
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