Instructions to use leafyseay/LaME-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leafyseay/LaME-2B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="leafyseay/LaME-2B")# Load model directly from transformers import LaMEMultimodal model = LaMEMultimodal.from_pretrained("leafyseay/LaME-2B", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 43db41f337fe2f55143c333528e26d019c6b4a3c79f1a0d1ebf0ad453bb0e178
- Size of remote file:
- 11.4 MB
- SHA256:
- adc6cd196ef9dad618795deafb95ae56fc64ee666216e71d1616f32be0c487b3
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