Lisper Gemma 4 E2B Audio Full Checkpoint
This is the merged Lisper checkpoint: google/gemma-4-E2B-it with the trained Lisper LoRA adapter folded into a standalone safetensors model.
Model Lineage
- Base model:
google/gemma-4-E2B-it - Training: Unsloth supervised fine-tuning with QLoRA / LoRA
- Merge method: base + LoRA adapter merged into a 16-bit checkpoint
- Weight file:
model.safetensors - Training rows:
16,000 - Validation rows:
2,000 - Held-out test rows:
2,000
This is not a dense full-parameter fine-tune. It is a merged base+LoRA checkpoint for easier deployment.
Evaluation
The release-quality evaluation is the v18 hybrid acoustic+Gemma path:
- Held-out rows:
2,000 - Hard errors:
0 - Verdict:
pass - Class match:
0.976 - Clear/non-clear match:
0.989 - Exact four-line format:
1.0 - Reason/cue/encouragement present:
1.0
The evaluated pipeline uses acoustic features for the lisp-class hint and Gemma for structured coaching text and tone. Do not interpret these metrics as a pure direct-Gemma raw-audio classification result.
Deployment
- Browser/WebGPU demo:
thomasjvu/lisper-gemma4-e2b-audio-onnx-q4f16 - Server-side ZeroGPU fallback:
thomasjvu/lisper-zerogpu - Adapter-only package:
thomasjvu/lisper-gemma4-e2b-audio-lora
Use the q4f16 ONNX/WebGPU package for browser demos. Use this merged checkpoint as the server-side correctness reference.
Limitations
- The lisp dataset is synthetically generated from speaker-disjoint source speech.
- This is a practice assistant, not a medical diagnosis tool or a replacement for a speech-language pathologist.
- Downloads last month
- 91