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mira2020
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Model Details
Model Provider
mira2020
Model Tree
google/gemma-4-E4B-it
Input Modalities
Output Modalities
Supported Functionality
/): repairs residual safety and clinical-boundary risks while preserving response quality and specificity./sft-refiner): rewrites unsafe drafts into supportive, specific, and professionally bounded responses.Both adapters use LoRA rank 8 over the language-model self-attention Q/K/V/O projections.
The system first generates a refined response using supervised fine-tuning. A selectively invoked risk-aware denoiser then repairs remaining violations using aspect-guided corruption, span-level risk-aware masking, and risk-weighted token-level training.
google/gemma-4-E4B-it
https://github.com/jordy9090/mh-denoise
This model is intended for research on mental-health response refinement, safety-aware generation, and parameter-efficient fine-tuning.
Generated responses may contain inaccurate or unsafe information. The model requires human review and appropriate safeguards in mental-health applications. It should not be used for diagnosis, treatment, medication guidance, crisis assessment, or emergency intervention.