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reservoir-agent-gpt2-batch
EmmaLeonhart/reservoir-agent-gpt2-batch
reservoir-agent-gpt2-batch is a machine learning model from EmmaLeonhart. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for reservoir-agent. The card lists the license as mit.
A batch of 4 reservoir agents (different fixed-random reservoir seeds) trained on the cross-pass recall task. A reservoir agent is a new model type: a pretrained transformer with a fixed reservoir brain-surgeried in (…
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Updated May 31, 2026
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.npz50.4 MB · 91%
At a glance
- Library
- reservoir-agent
- License
- mit
- Access
- Public
- Created
- May 31, 2026
- Updated
- May 31, 2026
- SHA
- 3f4bd551
Base models
Model card
From the Hugging Face model README
Reservoir Agent batch — gpt2
A batch of 4 reservoir agents (different fixed-random reservoir seeds)
trained on the cross-pass recall task. A reservoir agent is a new model type: a pretrained
transformer with a fixed reservoir brain-surgeried in (attended, cross-pass-stateful,
RNN-like) — see the project and
RESERVOIR_AGENTS.md.
The whole population is published, not just the winner. Reservoir performance is
stochastic in the seed; the suboptimal models are kept as signal for learning which
reservoir properties survive selection. The recommended model is seed_1.
Population
| rank | seed | recall | loss_end | pr_frac | recommended |
|---|---|---|---|---|---|
| 0 | seed_1 | 1.00 | 0.000 | 0.114 | yes |
| 1 | seed_0 | 1.00 | 0.001 | 0.114 | |
| 2 | seed_2 | 1.00 | 0.001 | 0.113 | |
| 3 | seed_3 | 1.00 | 0.200 | 0.112 |
Use
Each seed_<n>/ is a complete loadable reservoir agent. Load the recommended one:
from huggingface_hub import snapshot_download
from reservoir.persist import load_reservoir_model
path = snapshot_download("EmmaLeonhart/reservoir-agent-gpt2-batch")
lm = load_reservoir_model(f"{path}/seed_1")
batch_manifest.json records the ranking + each seed's score and reservoir-dynamics signal.
- Library
- reservoir-agent
- License
- mit
- Created
- May 31, 2026
- Updated
- May 31, 2026