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siddharthmb/2026.AP.cpt_ifp
2026.AP.cpt_ifp is a machine learning model from siddharthmb. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Main IFPruning continued-pretraining (CPT) run: Qwen2.5-3B with a Qwen2.5-0.5B predictor backbone and MLP head producing per-layer FFN masks (SoftTopK, tffn=1536 of 11008, ~1B activated params), maskmode=predictor, 30…
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Updated Aug 20, 2026
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From the Hugging Face model README
Main IFPruning continued-pretraining (CPT) run: Qwen2.5-3B with a Qwen2.5-0.5B predictor backbone and MLP head producing per-layer FFN masks (SoftTopK, t_ffn=1536 of 11008, ~1B activated params), mask_mode=predictor, 3000 steps (~0.8B tokens), warmup_mask_steps=500, lrs llm 2e-5 / predictor 5e-5 / head 1e-3.
Part of a replication of Apple's Instruction-Following Pruning for Large Language Models (arXiv:2501.02086) — "AP" = apple-paper-replicate, package ifpruning in Sid-MB/mats_exploration under code/apple-paper-replicate/ (branch introspection-causal-test, merged to main at a76965b).
head.pt) producing per-layer FFN importance scores [36, 11008]; per-row SoftTopK selects t_ffn=1536 of 11008 FFN units (~1B activated params). Dense-baseline runs train the same LLM without masking.checkpoints/step_3000/pytorch_model_fsdp_0/ — FSDP2 SHARDED_STATE_DICT model weights (llm + predictor_backbone + head)checkpoints/step_3000/optimizer_0/ — optimizer state (for exact training resumption)checkpoints/step_3000/random_states_*.pkl, scheduler.bin — RNG/scheduler statemodel/ — exported final model (llm/, predictor_backbone/, head.pt) from the FSDP export stepNo evaluations were run on this checkpoint. The project reached "scaffold + smoke test + this training grid" before being paused (see code/mats_exploration/everything we learned.md); logs/eval/ is empty and no eval_results directory exists. The only training-quality signal is the loss curves in the wandb runs below.
From code/ in the mats_exploration repo (paths as of June 2026; IFP_ROOT=/nlp/scr/siddharth/apple-paper-replicate set in slurm/_common.sh):
sbatch apple-paper-replicate/slurm/train.sbatch apple-paper-replicate/configs/presets/cpt_ifp.yaml
which runs (8 GPUs, accelerate FSDP2 full-shard bf16, SHARDED_STATE_DICT):
srun uv run accelerate launch --config_file apple-paper-replicate/configs/accelerate_fsdp8.yaml \
-m ifpruning.train --config apple-paper-replicate/configs/presets/cpt_ifp.yaml \
--ckpt-root $IFP_ROOT/ckpts --out-root $IFP_ROOT/models
Preset: configs/presets/cpt_ifp.yaml. Data: fineweb-edu sample-10BT, streaming, seq_len 4096. Seed 0. Slurm job 15878284 (jagupard37, preempted and resumed on jagupard39, 8 GPUs).
/nlp/scr2/siddharth/code/mats_exploration/code/apple-paper-replicate/logs/train/cpt_ifp_15878284.out/nlp/scr2/siddharth/apple-paper-replicate/ckpts/cpt_ifp (deleted after this upload was verified; this repo is now the only copy)/nlp/scr2/siddharth/code/mats_exploration/code/apple-paper-replicate/.../research-notes/2026-06-12_setup-and-smoke.md