Instructions to use privacy-tech-lab/LngModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use privacy-tech-lab/LngModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="privacy-tech-lab/LngModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("privacy-tech-lab/LngModel") model = AutoModelForSequenceClassification.from_pretrained("privacy-tech-lab/LngModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c4ff907d722b6e5da2b3d49ac1b341000307914f1499dbb173f8b195ebdf643
- Size of remote file:
- 3.12 kB
- SHA256:
- 2630d58d4bf2a88078369b2ecf8e7696990735475a4ef8f2ccaa44ac2c150d08
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