Instructions to use DavidHawksMSBA/Mod4Team12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DavidHawksMSBA/Mod4Team12 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DavidHawksMSBA/Mod4Team12")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DavidHawksMSBA/Mod4Team12") model = AutoModelForSequenceClassification.from_pretrained("DavidHawksMSBA/Mod4Team12", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c5a7036563d25253e35b899ae46b7acfe38297681e516621d439bfbc6ea7cf95
- Size of remote file:
- 557 MB
- SHA256:
- 2c3d87b81fa718e7dcf031ede4da44077e8c83b9d9ebc100377ae7d23eaa1b12
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