Text Classification
PEFT
Safetensors
English
Japanese
d1a
decision-model
calibration
lora
gemma4
typesafe
system-one
pull-requests
chat
on-device
Instructions to use JohnP1/d1a-e4b-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use JohnP1/d1a-e4b-it with PEFT:
from peft import PeftModel from transformers import AutoModel base_model = AutoModel.from_pretrained("google/gemma-4-E4B-it") model = PeftModel.from_pretrained(base_model, "JohnP1/d1a-e4b-it") - Notebooks
- Google Colab
- Kaggle
Download result.json from JohnP1/d1a-e4b-it: direct link, hf CLI and curl.
- Browser
- Download file 2.09 kB
-
https://huggingface.co/JohnP1/d1a-e4b-it/resolve/main/result.json
- Command line
-
hf download hf://JohnP1/d1a-e4b-it/result.json
-
curl -L -o result.json https://huggingface.co/JohnP1/d1a-e4b-it/resolve/main/result.json
2.09 kB
| { | |
| "model": "D1A-E4B-it v0.6", | |
| "temperature": 1.551, | |
| "method": "Every D1A suite (scripts/quality_gate.py --all-suites --sequential, then scripts/decide.py) on a Mac mini M4, 2026-10-17, against D1A-E2B-it v0.6, both as served: MLX 8-bit unmerged chat builds with media, each at its own temperature. Paired bootstrap 95% intervals. Live PR-labeler replay and hand-labelled PRs are private; aggregates only.", | |
| "suites": { | |
| "decision-v7": [ | |
| 1264, | |
| 84.8, | |
| 85.7, | |
| "+0.9 [-0.7,+2.5]" | |
| ], | |
| "transfer-v4": [ | |
| 656, | |
| 75.0, | |
| 77.4, | |
| "+2.4 [-0.9,+5.9]" | |
| ], | |
| "hard-v1": [ | |
| 1083, | |
| 69.2, | |
| 75.7, | |
| "+6.6 [+4.0,+9.2]" | |
| ], | |
| "devtools-v1": [ | |
| 1074, | |
| 71.1, | |
| 74.3, | |
| "+3.2 [+0.9,+5.4]" | |
| ], | |
| "documents-v1": [ | |
| 920, | |
| 86.3, | |
| 88.6, | |
| "+2.3 [+0.5,+4.2]" | |
| ], | |
| "ja-jglue:development": [ | |
| 1500, | |
| 78.6, | |
| 80.8, | |
| "+2.2 [+0.5,+4.0]" | |
| ], | |
| "ja-jglue:test": [ | |
| 1500, | |
| 76.4, | |
| 78.6, | |
| "+2.2 [+0.3,+4.1]" | |
| ], | |
| "pr-labels:test": [ | |
| 2045, | |
| 77.4, | |
| 79.1, | |
| "+1.8 [+0.5,+3.1]" | |
| ], | |
| "pr-labels:test sev+offsets": [ | |
| 953, | |
| 64.3, | |
| 69.5, | |
| "+5.1 [+3.0,+7.3]" | |
| ], | |
| "pr-labels:development": [ | |
| 2030, | |
| 78.8, | |
| 79.6, | |
| "+0.8 [-0.4,+2.1]" | |
| ], | |
| "pr-labels:test-ja": [ | |
| 193, | |
| 74.6, | |
| 77.7, | |
| "+3.1 [-1.0,+7.2]" | |
| ], | |
| "routing:factory-development": [ | |
| 640, | |
| 92.3, | |
| 93.6, | |
| "+1.2 [-0.7,+3.2]" | |
| ], | |
| "routing:generic-development": [ | |
| 270, | |
| 97.0, | |
| 97.4, | |
| "+0.4 [-1.5,+2.2]" | |
| ], | |
| "external:typesafe-v1": [ | |
| 102, | |
| 69.6, | |
| 86.3, | |
| "+16.7 [+8.8,+25.2]" | |
| ], | |
| "external:wanli-v2": [ | |
| 1002, | |
| 68.9, | |
| 72.7, | |
| "+3.8 [+1.4,+6.2]" | |
| ], | |
| "night2:dates": [ | |
| 900, | |
| 87.0, | |
| 90.8, | |
| "+3.8 [+1.7,+5.8]" | |
| ], | |
| "night2:unknowable": [ | |
| 525, | |
| 69.5, | |
| 66.7, | |
| "-2.9 [-5.5,-0.2]" | |
| ] | |
| }, | |
| "columns": [ | |
| "n", | |
| "E2B-it v0.6 accuracy %", | |
| "E4B-it v0.6 accuracy %", | |
| "delta [95% CI]" | |
| ], | |
| "pooled_delta": "+2.5 [+1.7, +3.4] over 21 suite lines and 2 live", | |
| "latency_ratio_vs_e2b_it": 2.94, | |
| "media": "14 photo/voice/video demo requests, 28 answers, all answered; 7 differ from E2B-it, 6 better and 1 worse by hand read" | |
| } |