Instructions to use nvidia/C-RADIO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/C-RADIO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="nvidia/C-RADIO", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nvidia/C-RADIO", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload model
Browse files- hf_model.py +1 -0
hf_model.py
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@@ -24,6 +24,7 @@ from .common import RESOURCE_MAP, DEFAULT_VERSION
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# Import all required modules.
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from .adaptor_base import AdaptorBase, RadioOutput, AdaptorInput
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from .adaptor_registry import adaptor_registry
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from .enable_cpe_support import enable_cpe
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from .enable_spectral_reparam import configure_spectral_reparam_from_args
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from .eradio_model import eradio
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# Import all required modules.
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from .adaptor_base import AdaptorBase, RadioOutput, AdaptorInput
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from .adaptor_registry import adaptor_registry
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from .cls_token import ClsToken
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from .enable_cpe_support import enable_cpe
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from .enable_spectral_reparam import configure_spectral_reparam_from_args
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from .eradio_model import eradio
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