Instructions to use privacy-tech-lab/LatModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use privacy-tech-lab/LatModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="privacy-tech-lab/LatModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("privacy-tech-lab/LatModel") model = AutoModelForSequenceClassification.from_pretrained("privacy-tech-lab/LatModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f099c70de956986b7db40b584216520c5b8d95548cbec2f488b6fe94ef911b5
- Size of remote file:
- 3.12 kB
- SHA256:
- 683a161749944e24966937f4f2264ac222e05e78ef8d2b137681485df6e0fbb0
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