mydeskmate/grammar-v7d
AI model by mydeskmate
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Model card & documentation
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T5-base (220M) grammar correction model, continued from grammar-v7b lineage with a 12% dose of exam-style calibration data (the "dose ladder" sweet spot). Promotion rule (written BEFORE the run): keep only if (CoNLL > 47.35 or BEA > 33.90) AND JFLEG GLEU >= 62.30 AND Do-No-Harm < 5%. All four gates passed: Measured through the exact production engine on CPU (threads=2): productionbenchmarkv7d.json (battery), logs/v7dortsuite.log (probe). scorers — published with raw JSON at mydeskmate/gec-bench) Our row above = the pre-registered GPU PyTorch promotion run (beams=4). The live ONNX int8 serving run of the same model reads 62.61 / 49.34 / 34.61 with the 500-sentence probe at 4.20% — see the…
Read the full model card ↗ · Preview checked 2026-10-28T02:18:53.160Z
Inside the original model card — Document outline
- grammar-v7d — MyDeskMate English Grammar Checker (run #4, PASSED)
- Pre-registered promotion record (run #4, 26–29 Sep 2026 GPU + local verify)
- Live serving path (ONNX Runtime int8, greedy, this repo's graphs)
- Head-to-head (Phase 1, all systems measured in OUR lab through OUR official
- Open targets (unbeaten rows)
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Model overview
mydeskmate/grammar-v7d is a task-unspecified model repository published by mydeskmate on Hugging Face. A library was not reported.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- Not reported
- Library
- Not reported
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 222,903,552
- Architecture
- T5ForConditionalGeneration
- License
- Not reported — check the model card
- Access
- Not gated by Hugging Face
- Created
- 2026-10-19T06:35:24.000Z
- Last modified
- 2026-10-19T06:35:51.000Z
Compatibility and lineage
Language coverage was not reported.
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-19T06:43:13.200Z. Daily imports are snapshots, not real-time monitoring.
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