Instructions to use pszmk/lamp-grugru-vae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pszmk/lamp-grugru-vae with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="pszmk/lamp-grugru-vae", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("pszmk/lamp-grugru-vae", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 225 Bytes
8d93a9a | 1 2 3 4 5 6 7 8 9 10 11 12 13 | from transformers import AutoModel
MODEL_ID = "pszmk/lamp-grugru-vae"
REVISION = "main"
model = AutoModel.from_pretrained(
MODEL_ID,
revision=REVISION,
trust_remote_code=True,
)
print(model.__class__.__name__)
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