Instructions to use matth/flowformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use matth/flowformer with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("matth/flowformer", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add reference to config class
Browse files- model_flowformer.py +2 -0
model_flowformer.py
CHANGED
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@@ -71,6 +71,8 @@ class Flowformer(PreTrainedModel):
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Initializing with a config file does not load the weights associated with the model, only the
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configuration. Check out the [`~PreTrainedModel.from_pretrained`] method to load the model weights.
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"""
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def __init__(self, config: FlowformerConfig):
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super().__init__(config)
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Initializing with a config file does not load the weights associated with the model, only the
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configuration. Check out the [`~PreTrainedModel.from_pretrained`] method to load the model weights.
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"""
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+
config_class = FlowformerConfig
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def __init__(self, config: FlowformerConfig):
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super().__init__(config)
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