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tags:
- artificial-life
- embodied-ai
- mechanistic-interpretability
- babyllm
- pytorch
---
# Project Mochi — published bridge checkpoints
This repository contains **small Project Mochi bridge checkpoints**, not standalone language models.
A Mochling combines a frozen BabyLM ancestor with learned sensorimotor projection layers, action heads, a target-pointer head, episodic-memory projection, caretaker perception, and working interaction state. The bridge checkpoints here are intended to be loaded by the Project Mochi codebase.
## Upstream ancestor
Current published bridges target:
`qyxu1994/instanton-childes-heavy`
The ancestral Transformer remains frozen during Project Mochi bridge training.
## Published artifacts
| Checkpoint | File | SHA-256 | Meaning |
|---|---|---|---|
| MVP-0.7b | `childes_mvp07b_bridge.pt` | `e23ea741d66170298dd16b78b823ceb9006311622d83a22d7364156d1d621235` | Working interaction state + episodic-memory sensorimotor bridge |
| MVP-0.10 | `childes_mvp010_bridge.pt` | `768e476750af3b449ab6739a9801883f29f66532535b6f8ccc9c1c7fc59cb922` | Caretaker embodiment + PUSH + language-conditioned motor control |
| MVP-0.11 | `childes_mvp011_bridge.pt` | `03b754aa1179c046b416e8acf701ab1e7caeda587c2a7877fa09e8b163d63abb` | Environment-dynamics bridge (event novelty, need-modulated reward, seeded layouts) |
Not every experimental run is published. The policy is to publish checkpoints at scientifically meaningful milestone boundaries.
## Usage
The preferred path is through the Project Mochi launcher:
```bash
pip install -e .
mochi-terrarium
```
If the requested named checkpoint is not available locally, the launcher fetches the exact artifact from this repository and records a local SHA-256 provenance sidecar.
Explicit fetch:
```bash
python3 scripts/fetch_checkpoint.py --checkpoint-id mvp-0.10
```
Project source:
`https://github.com/anicka-net/mochlings`
## Scientific scope
### MVP-0.10 language result
MVP-0.10 includes supervised **language-conditioned motor grounding**: matched referential text such as colour words causally shifts the physical target-pointer distribution in held-out synthetic evaluations.
It does **not** yet include a supervised next-token speech objective. The current speech-generation path is an experimental ancestral BabyLM generation conditioned on grounded sensory prefixes and dialogue context. It should not be interpreted as a separately trained grounded speech policy.
### Caretaker embodiment
The caretaker is represented by an explicit structured percept rather than a hidden target override. Pointing, touch, and holding can enter the neural prefix as observable interaction signals.
## Architecture / provenance
The checkpoints contain Project Mochi bridge parameters only. They do **not** vendor the ~27M ancestral model weights.
See the source repository for:
- milestone reports and quantitative evaluation;
- architecture and perception-boundary invariants;
- checkpoint loader implementation;
- exact training curricula;
- third-party licence and dataset-provenance notes.
## Licensing and upstream-data note
The upstream Instanton model code and weights are documented as MIT-licensed (`docs/licensing_third_party.md`). However, the BabyLM training mixture includes upstream corpora with heterogeneous terms, including research/non-commercial restrictions. Do not assume the ancestral training corpus is commercially unencumbered or redistributable.
See `docs/licensing_third_party.md` in the Project Mochi source repository for third-party provenance details.
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