A DSpark speculative-decoding drafter (block size 8, 3 layers, reduced draft vocabulary 32000) for the target model open-athena/Grug-67B-A2B-Datakit-SFT-262K-2026.09.21. Trained with the speculators library (fork atutej/speculators, branch grug-dspark-gate); run name dsparkgrug-67b-a2b-datakit-sftdatakit-sft-mixtargetgen. targetgen drafter (target-generated): trained on the target's own replies. 270,000 Datakit conversations (4.2% of the train split, sampled uniformly with seed 0 from the dataset in trainingdatamanifest.json) were regenerated turn by turn by the target in vLLM at T=1 (up to 32,768 new tokens per turn; original tool outputs and later user turns kept as context), giving…
Independent publisher
Atula Tejaswi
atutej
Models in Library2
Datasets in Library0
Models on Hugging Face14
Followers1
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Models
A DSpark speculative-decoding drafter (block size 8, 3 layers, reduced draft vocabulary 32000) for the target model open-athena/Grug-67B-A2B-Datakit-SFT-262K-2026.09.21. Trained with the speculators library (fork atutej/speculators, branch grug-dspark-gate); run name dsparkgrug-67b-a2b-datakit-sftdatakit-sft-mixitw. itw drafter (in-the-wild text): trained on the gold replies of the Datakit SFT mix, the data the target was fine-tuned on, as written and with no regeneration. This is a mid-run checkpoint at step 80,813 (21% of one epoch of 382,747 steps, about 9.7B tokens, 12 h on 2 GB200 nodes); training was stopped by a time limit before the learning rate had decayed. The trainer's…