Instructions to use jinaai/jina-bert-flash-implementation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jinaai/jina-bert-flash-implementation with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jinaai/jina-bert-flash-implementation", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
fix: fixed typo
Browse files- modeling_lora.py +1 -1
modeling_lora.py
CHANGED
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@@ -101,7 +101,7 @@ class BertLoRA(BertPreTrainedModel):
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return self.bert(*args, **kwargs)
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def parameters(self, recurse: bool = True) -> Iterator[Parameter]:
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-
for
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yield param
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def named_parameters(
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return self.bert(*args, **kwargs)
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def parameters(self, recurse: bool = True) -> Iterator[Parameter]:
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+
for _, param in self.named_parameters(recurse=recurse):
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yield param
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def named_parameters(
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