Instructions to use bigshanedogg/Concerto-Tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bigshanedogg/Concerto-Tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="bigshanedogg/Concerto-Tiny", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bigshanedogg/Concerto-Tiny", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 498 Bytes
b25b243 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | """Concerto processor: ``ConcertoFeatureExtractor`` (the package's inference transform) as its only part."""
from transformers.processing_utils import ProcessorMixin
class ConcertoProcessor(ProcessorMixin):
attributes = ["feature_extractor"]
def __init__(self, feature_extractor=None, **kwargs):
super().__init__(feature_extractor, **kwargs)
def __call__(self, point=None, **kwargs):
return self.feature_extractor(point, **kwargs)
__all__ = ["ConcertoProcessor"]
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