Diffusion LFM2.5 24B-A2B โ€” e-means LoRA merged

This revision contains an experimental merge of the e-means code-generation LoRA into the base model.

Contents

  • Merged BF16 model weights
  • Tokenizer and configuration
  • Learned diffusion mask embedding: diffusion.safetensors
  • Custom diffusion implementation: modeling_diffusion_lfm.py
  • Merge validation: merge_validation.json

Important validation warning

This checkpoint is experimental.

The merge completed and no LoRA parameters remained. The 10 bidirectional attention modules retained is_causal=False.

However:

  • Maximum pre/post merge logits difference: 1.662109
  • Mean pre/post merge logits difference: 0.182571
  • Top-1 agreement on the tested probe: 100%
  • Strict numerical equivalence: NOT PASSED
  • Local merged checkpoint reload: NOT VERIFIED
  • Code-generation quality: NOT VERIFIED

The original custom diffusion loader may require adaptation to load the merged safetensors format.

The original revision is preserved in a backup branch. Consult the repository branch history before using this checkpoint in production.

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