Instructions to use TiffanyH/final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TiffanyH/final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TiffanyH/final")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TiffanyH/final") model = AutoModelForSequenceClassification.from_pretrained("TiffanyH/final", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0cc2a97b7814a6dd5b9f0fe8c4560fe1ae4c80feab9ceffe9354f30b7daabbb3
- Size of remote file:
- 438 MB
- SHA256:
- be30459566377ad59896845657873f3e9bf39b8f46e98b611bbc3cfb5f112504
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