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README.md

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+---
+license: apache-2.0
+base_model: allenai/Olmo-3-7B-Instruct
+library_name: pushpuppet
+pipeline_tag: text-generation
+tags:
+  - pushpuppet
+  - olmo3
+  - adaptive-inference
+  - structured-pruning
+  - elastic-model
+---
+
+# PushPuppet · Olmo-3-7B-Instruct (post-RL)
+
+A **push-puppet** checkpoint fitted on top of
+[`allenai/Olmo-3-7B-Instruct`](https://huggingface.co/allenai/Olmo-3-7B-Instruct).
+
+This is **not** a drop-in `transformers` model. It is a *gated* checkpoint: the
+base network is augmented with learned per-unit gates (B-spline gate curves over
+FFN neurons and attention heads) so that a **single** set of weights yields a
+whole family of valid subnetworks, indexed by a compression control variable
+**λ**. Raising λ prunes more units; the gates were trained (mid-train → SFT → RL)
+so every rung of the ladder stays a usable model.
+
+It is intended to be served by the
+[PushPuppet adaptive runtime](https://github.com/saudiwin/pushpuppet_runtime),
+which picks λ from available memory at runtime and serves the resulting
+subnetwork over an OpenAI-compatible API.
+
+## Files
+
+| File | Size | What it is |
+|---|---|---|
+| `model.pt` | ~27 GiB | Bare `torch.save` state dict, fp32, gates included |
+| `train_args.json` | — | Records the base model id so the runtime can fetch config + tokenizer |
+
+`model.pt` is a plain state dict (no config, no tokenizer). The runtime pulls
+`config.json` and the tokenizer from the base repo named in `train_args.json`.
+
+## Architecture
+
+Matches `allenai/Olmo-3-7B-Instruct` exactly, plus gate parameters:
+
+| | |
+|---|---|
+| params | 7.30 B (fp32) |
+| layers | 32 |
+| hidden / intermediate | 4096 / 11008 |
+| attention | 32 query / 32 KV heads (MHA), head_dim 128, per-head QK norm |
+| vocab | 100278 |
+| max context | 65536 (YaRN, ×8 over 8192) |
+
+Push-puppet gate hyperparameters (inferable from the tensors, so you don't have
+to supply them): `n_knots=8`, `degree=3`, per-head QK norm enabled,
+`scale_output=true`.
+
+## Usage
+
+```bash
+git clone https://github.com/saudiwin/pushpuppet_runtime
+cd pushpuppet_runtime
+uv sync --extra torch
+
+scripts/download_model.sh          # fetches this repo into models/olmo3_7b_instruct_post_rl
+uv run pushpuppet up --ckpt-dir models/olmo3_7b_instruct_post_rl --lambda 1 --save
+```
+
+The runtime then serves an OpenAI-compatible API on `http://localhost:11435/v1`
+plus a live dashboard at `http://localhost:11435/`, where you can move λ up and
+down and watch the footprint change.
+
+At ~27 GiB the checkpoint trips the runtime's **disk-first** loader
+automatically (threshold 20 GiB): the state dict is memory-mapped and the pruned
+model is materialized one layer at a time, so peak RAM is roughly the *pruned*
+model rather than the dense one. Default precision is bf16; add
+`--quantize int8` to roughly halve it again.
+
+### Loading it yourself
+
+You need the `push_puppet` research repo for the gate modules — the state dict
+references `inject_stochastic_mlp` / `inject_stochastic_attn` parameters that
+stock `transformers` does not define:
+
+```python
+import torch, sys
+from transformers import Olmo3Config, Olmo3ForCausalLM
+sys.path.insert(0, "/path/to/push_puppet/python")
+import olmo3_mini_train as train_mod
+
+cfg = Olmo3Config.from_pretrained("allenai/Olmo-3-7B-Instruct")
+model = Olmo3ForCausalLM(cfg)
+train_mod.inject_stochastic_mlp(model, temperature=0.5, n_knots=8, degree=3)
+train_mod.inject_stochastic_attn(model, temperature=0.5, n_knots=8, degree=3)
+train_mod.inject_per_head_qk_norm(model)
+model.load_state_dict(torch.load("model.pt", map_location="cpu", weights_only=True))
+```
+
+Then call `structural_prune(model, lam)` to get a dense subnetwork at a given λ.
+
+(`temperature=0.5` here is the **gate** temperature — the runtime's default, and
+unrelated to sampling temperature at generation time.)
+
+## License
+
+Apache 2.0, inherited from the base model `allenai/Olmo-3-7B-Instruct`.

model.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5c6912e6a08ebaeb253204749f4022c3dc39a4e3e3f3f54b08a329d0ea305f4f
+size 29194731375

train_args.json

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+{
+  "model_id": "allenai/Olmo-3-7B-Instruct"
+}