fix: add missing lora adaptations

#8
Files changed (1) hide show
  1. custom_st.py +9 -0
custom_st.py CHANGED
@@ -56,6 +56,15 @@ class Transformer(nn.Module):
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  config = AutoConfig.from_pretrained(model_name_or_path, **config_args, cache_dir=cache_dir)
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  self.auto_model = AutoModel.from_pretrained(model_name_or_path, config=config, cache_dir=cache_dir, **model_args)
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  if max_seq_length is not None and "model_max_length" not in tokenizer_args:
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  tokenizer_args["model_max_length"] = max_seq_length
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  self.tokenizer = AutoTokenizer.from_pretrained(
 
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  config = AutoConfig.from_pretrained(model_name_or_path, **config_args, cache_dir=cache_dir)
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  self.auto_model = AutoModel.from_pretrained(model_name_or_path, config=config, cache_dir=cache_dir, **model_args)
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+ self._lora_adaptations = config.lora_adaptations
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+ if (
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+ not isinstance(self._lora_adaptations, list)
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+ or len(self._lora_adaptations) < 1
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+ ):
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+ raise ValueError(
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+ f"`lora_adaptations` must be a list and contain at least one element"
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+ )
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+
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  if max_seq_length is not None and "model_max_length" not in tokenizer_args:
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  tokenizer_args["model_max_length"] = max_seq_length
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  self.tokenizer = AutoTokenizer.from_pretrained(