Comments (2)
Able to find the problem and the solution.
# Modified for peft related changes that were missing in the original version
if _is_peft_model(self.model):
if hasattr(self.model, "get_base_model"):
model_to_inspect = self.model.get_base_model()
default_label_names = find_labels(model_to_inspect.__class__)
self.can_return_loss = can_return_loss(model_to_inspect.__class__)
else:
default_label_names = find_labels(self.model.__class__)
self.can_return_loss = can_return_loss(self.model.__class__)
self.label_names = default_label_names if self.args.label_names is None else self.args.label_names
self.control = self.callback_handler.on_init_end(self.args, self.state, self.control)
# End of modification
Need to convert to PR so that can pull and make these changes
from transformers.
The issue is fixed using the code that is updated on trainer and sent as part of pull request
from transformers.
Related Issues (20)
- ValueError: Cannot use apply_chat_template() because tokenizer.chat_template is not set and no template argument was passed! For information about writing templates and setting the tokenizer.chat_template attribute, please see the documentation HOT 1
- TypeError: '<' not supported between instances of 'NoneType' and 'int' HOT 2
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- batch inference scales linearly with batch size when input is long HOT 1
- Exception raised with trainer + `accelerate launch` FSDP + large gradient accumulation steps + small dataset
- Do Transformers onnx export support the input of the Llama is the input_embeds? HOT 1
- Cannot batch them ({'num_frames', 'input_features', 'is_last'} != {'input_features', 'is_last'}) HOT 1
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- Try to convert LlamaForCausalLM to ONNX with input_embeds as input
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- FileNotFoundError: Unable to Create Symlink in `cache_dir` - No Such File or Directory HOT 2
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- Character sets not supported on windows11 HOT 10
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from transformers.