Instructions to use open-athena/marinfold-exp166 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use open-athena/marinfold-exp166 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("open-athena/marinfold-exp166", device_map="auto") - Notebooks
- Google Colab
- Kaggle
MarinFold exp166 checkpoints
Final checkpoints from the MarinFold contacts-v1 1.5B amino-acid augmentation
experiment tracked in
Open-Athena/MarinFold#166.
Loss is eval/tokenized/contacts-v1-val/loss.
Both checkpoint formats are retained:
hf/contains aQwen3ForCausalLMHugging Face safetensors export with the contacts-v1 tokenizer colocated with the weights.checkpoints/contains the original Levanter OCDBT checkpoint for training restart or re-export.
Checkpoint inventory
| Epochs | Initialization | Selection | W&B run | Loss | Step | Repository paths | Full GCS sources |
|---|---|---|---|---|---|---|---|
| 8 | exp117 checkpoint | Final | prot-exp166-cv1-aaaug-1_5b-e8-lr3p162e-3-wd0p1-bs128-exp117-init-us-east1 |
2.664179 | 35,679 | Levanter: checkpoints/step-35679HF: hf/step-35679 |
Levanter: gs://marin-us-east1/prot-exp166-cv1-aaaug-1_5b-e8-lr3p162e-3-wd0p1-bs128-exp117-init-us-east1/2026.07.27.1/checkpoints/step-35679/HF: gs://marin-us-east1/prot-exp166-cv1-aaaug-1_5b-e8-lr3p162e-3-wd0p1-bs128-exp117-init-us-east1/2026.07.27.1/hf/step-35679/ |
The training target was 35,680 steps; Levanter's zero-indexed final checkpoint
is step-35679. The dated GCS layout component is intentionally omitted from
repository paths.
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