Instructions to use modrill/rstar_coder_32m_lora_olmo3_1025_7b_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use modrill/rstar_coder_32m_lora_olmo3_1025_7b_base with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("allenai/Olmo-3-1025-7B") model = PeftModel.from_pretrained(base_model, "modrill/rstar_coder_32m_lora_olmo3_1025_7b_base") - Notebooks
- Google Colab
- Kaggle
rstar_coder_32m_lora_olmo3_1025_7b_base
Immutable LoRA adapter freeze (ADAPTER_ONLY_NO_MERGE).
- Base:
allenai/Olmo-3-1025-7B@a81bae42db3975be1671e27b9c9a56da1a9f980f - Adapter tree SHA-256:
4964d87b49be67f1b80a626c5ded0c482c69553ec6799eda2d073e0f8e9e2569 - Immutable tag:
freeze-4964d87b49be67f1 - Dose: 32018321 assistant target tokens (step 419)
- Recipe SHA-256:
b2fb6275575e08e1b07d482d9f12418b22f5588c55b28bbf9dec29fb3e1fadf9 - Data READY manifest SHA-256:
397e8ba94a5d421ee960344e3e45e431ea90174ff9c0e459f5d9bb57137caf97 - DEV256 (seed 3407): pass@1 = 0.2734375 (70/256)
- Trained on GPU: 1
Do not merge unless you intentionally create a separate merged revision. Load with PEFT against the pinned base revision above.
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Model tree for modrill/rstar_coder_32m_lora_olmo3_1025_7b_base
Base model
allenai/Olmo-3-1025-7B