SFTTrainer
Raises NotImplementedError with IterableDataset
#2138
Labels
🐛 bug
Something isn't working
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🏋 SFT
Related to SFT
System Info
Google Colab
Description
When attempting to fine-tune a model using the
SFTTrainer
with anIterableDataset
, an error occurs because theSFTTrainer
expects a dataset that supports random access (__getitem__
). This is problematic when working with large datasets that cannot be loaded into memory at once and require streaming.Error Message
Context : This issue is especially relevant for fine-tuning on very large datasets, where memory constraints make it impractical to load the dataset fully into memory.
Information
Tasks
examples
folderReproduction
Expected behavior
The
NotImplementedError
is raised when the trainer tries to access the dataset.The text was updated successfully, but these errors were encountered: