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Add custom prepare_for_training logic to ECD model for LLM encoder adapter initialization #3874

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merged 4 commits into from
Jan 11, 2024

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jeffkinnison
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The LLM model type initializes the adapter weights and quantization at training time using LLM.prepare_for_training. When LLMEncoder was added, ECD model did not have a corresponding prepare_for_training method, so adapter initialization occurred at encoder initialization. This PR adds ECD.prepare_for_training, which brings LLMEncoder adapter initialization to parity with LLM models.

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github-actions bot commented Jan 10, 2024

Unit Test Results

  6 files  ±0    6 suites  ±0   14m 13s ⏱️ -6s
12 tests ±0    9 ✔️ ±0    3 💤 ±0  0 ±0 
60 runs  ±0  42 ✔️ ±0  18 💤 ±0  0 ±0 

Results for commit 768aaaf. ± Comparison against base commit 89a032f.

♻️ This comment has been updated with latest results.

@arnavgarg1 arnavgarg1 merged commit e7d86e4 into master Jan 11, 2024
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@arnavgarg1 arnavgarg1 deleted the llm-encoder-prepare-for-training branch January 11, 2024 17:26
@jeffkinnison jeffkinnison changed the title Add custom prepare_for_trianing logic to ECD model for LLM encoder adapter initialization Add custom prepare_for_training logic to ECD model for LLM encoder adapter initialization Jan 16, 2024
vijayi1 pushed a commit to vijayi1/ludwig that referenced this pull request Jan 23, 2024
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3 participants