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lucapinello/chorus-borzoi
chorus-borzoi is a machine learning model from lucapinello. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Mirror of the Borzoi 4-fold ensemble. The flashzoi PyTorch port repos at johahi/borzoi-replicate-{0..3} are the canonical chorus source; this mirror under the chorus org consolidates weight provenance alongside Enform…
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Updated Apr 30, 2026
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From the Hugging Face model README
Mirror of the Borzoi 4-fold ensemble. The flashzoi PyTorch port repos at
johahi/borzoi-replicate-{0..3} are the canonical chorus source; this
mirror under the chorus org consolidates weight provenance alongside
Enformer, Sei, LegNet, and ChromBPNet for resilience.
The weights were copied from the johahi flashzoi PyTorch port (which in turn ports the original Calico Labs Borzoi TensorFlow checkpoints). Those weights were created by Calico Labs and are the property of Calico Life Sciences LLC.
The model parameters, outputs, and any derivatives thereof remain subject to the original Borzoi release license (Apache 2.0 per https://github.com/calico/borzoi).
The flashzoi PyTorch port (the actual loader code that consumes these
files) is also Apache 2.0; chorus's loader at chorus.oracles.borzoi
is released under the chorus license. These terms are consistent with
the terms for the reference code and the model weights.
fold_0/ — fold 0 PyTorch state_dict + config.jsonfold_1/ — fold 1fold_2/ — fold 2fold_3/ — fold 3Total: ~6 GB (each fold has both model.safetensors and the legacy
pytorch_model.bin for compatibility).
In chorus ≥ 0.4 the BorzoiOracle fetches the requested fold from this
HF repo by default and falls back to johahi's original repos if HF is
unreachable.
from huggingface_hub import snapshot_download
local = snapshot_download(repo_id="lucapinello/chorus-borzoi", repo_type="model",
allow_patterns=["fold_0/*"])