Draft: Save resume lora ckpt #6
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Signed-off-by: vineet <[email protected]>
Signed-off-by: vineet <[email protected]>
Signed-off-by: vineet <[email protected]>
Signed-off-by: vineet <[email protected]>
Signed-off-by: vineet <[email protected]>
Signed-off-by: vineet <[email protected]>
Signed-off-by: vineet <[email protected]>
Signed-off-by: vineet <[email protected]>
…lation Signed-off-by: vineet <[email protected]>
Signed-off-by: vineet <[email protected]>
Signed-off-by: vineet <[email protected]>
This PR adds checkpointing for fine-tuning: - Add checkpoint saving every N steps with --checkpoint-save-steps - Save complete training state: model weights, optimizer state, metadata - Implement two-phase optimizer state loading to avoid memory issues - Add --resume-from-checkpoint and --auto-resume functionality - Store optimizer momentum/variance tensors in GGUF format - Add checkpoint validation for rank, alpha, and target modules - Update README.md with checkpointing documentation The optimizer state loading: iteration count is loaded during initialization, while tensor data (grad_m, grad_v) is loaded after ggml_opt_alloc creates the proper tensor structures.
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This PR adds support for saving a checkpoint after N train steps and resuming training from any of the saved checkpoints.