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gemma-3-270m-it-dynamicplp
edorazio/gemma-3-270m-it-dynamicplp
gemma-3-270m-it-dynamicplp is a text generation model from edorazio. Use it when you need the model to write or continue text. It is set up for transformers.js. The card lists the license as gemma.
Fine-tuned Gemma 3 270M IT for in-browser e-commerce user profiling. Designed to run client-side in DynamicPLP via Transformers.js + WebGPU.
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.onnx4.5 GB · 99%
At a glance
- Task
- Text Generation
- Library
- transformers.js
- License
- gemma
- Model type
- gemma3_text
- Access
- Public
- Created
- Apr 17, 2026
- Updated
- Apr 17, 2026
- SHA
- 525dc4dc
Base models
Model card
From the Hugging Face model README
Gemma 3 270M — DynamicPLP Profiler
Fine-tuned Gemma 3 270M IT for in-browser e-commerce user profiling. Designed to run client-side in DynamicPLP via Transformers.js + WebGPU.
Task
Analyzes shoe-browsing interaction logs and assigns preference weights across 3 dimensions:
- Colors (23 values):
rosso, blu, nero, beige, ... - Styles (6 values):
casual, classic, elegant, minimal, sporty, urban - Categories (6 values):
flat, high_heel, hiking_boot, mans_shoe, running, womans_boot
Output format (6 lines, Italian):
COLOR colore=peso, colore=peso
STYLE stile=peso, stile=peso
CATEGORY categoria=peso, categoria=peso
CONFIDENCE 0.0-1.0
INTENT exploring|deciding|focused
MESSAGE <1-2 Italian sentences>
Training
- Teacher:
mlx-community/gemma-4-e4b-it-4bit(Gemma 4 E4B with thinking enabled) - Dataset: 1071 synthetic browsing sessions, strictly whitelist-filtered
- Method: LoRA (rank=16, scale=2.0) on q/k/v/o projections, all layers
- Optimizer: AdamW, lr=1e-4, 1000 iters, batch=4
- Framework: mlx-lm → ONNX via optimum
Eval (161 holdout examples)
| Metric | Value |
|---|---|
| Format compliance | 100% |
| Invalid labels | 2.5% |
| Color cosine sim vs teacher | 0.72 |
| Style cosine sim vs teacher | 0.77 |
| Category cosine sim vs teacher | 0.78 |
| Intent accuracy (deciding) | 100% |
| Confidence MAE | 0.061 |
| Gen speed (MLX bf16) | 0.58s/ex |
Known limitation: training data was 91% deciding intent. Student collapses minority intents (exploring, focused → 0% recall). Reordering quality (weights) unaffected; intent only impacts trigger cooldown in DynamicPLP.
Files
| File | Size | Use |
|---|---|---|
onnx/model.onnx | 1.6 GB | fp32 reference |
onnx/model_fp16.onnx | 1.3 GB | CPU fallback |
onnx/model_q4.onnx | 800 MB | fp32 activations + 4-bit weights |
onnx/model_q4f16.onnx | 481 MB | WebGPU primary |
Usage in Transformers.js
import { pipeline } from '@huggingface/transformers';
const pipe = await pipeline(
'text-generation',
'edorazio/gemma-3-270m-it-dynamicplp',
{ dtype: 'q4f16', device: 'webgpu' }
);
License
Gemma Terms of Use. See https://ai.google.dev/gemma/terms
- Task
- Text Generation
- Library
- transformers.js
- Type
- gemma3_text
- License
- gemma
- Languages
- it
- Created
- Apr 17, 2026
- Updated
- Apr 17, 2026