--- license: apache-2.0 base_model: allenai/Olmo-3-1025-7B tags: - code - reasoning - lora-merged - livecodebench pipeline_tag: text-generation library_name: transformers --- # code-think-o7b-20260908 Research checkpoint: **allenai/Olmo-3-1025-7B** (`a81bae42db3975be1671e27b9c9a56da1a9f980f`) after V4 LoRA SFT on Qwen3-30B-A3B-Thinking-2507 traces (OLMo-tokenized V4 payload), then merged to full weights. Repo name uses **OLMo-3** because `RUN_IDENTITY.model.hf_id` is `allenai/Olmo-3-1025-7B` (not OLMo-2). This is a **research checkpoint, not a product**. Single-seed diagnostic numbers only. Do not treat DEV256 as a leaderboard claim. License: **Apache-2.0**, inherited from [allenai/Olmo-3-1025-7B](https://huggingface.co/allenai/Olmo-3-1025-7B) (verified from the local base `README.md`: `license: apache-2.0`). ## Base, teacher, and data | | | |---|---| | Student | `allenai/Olmo-3-1025-7B` revision `a81bae42db3975be1671e27b9c9a56da1a9f980f` | | Teacher | `Qwen/Qwen3-30B-A3B-Thinking-2507` traces (V4 paired think payload, OLMo renderer / tokenizer) | | Problems | **4715** unique problems (`source_1ep_rows`); physical 2-epoch concat = **9430** rows | | Dose | **31,689,386** assistant tokens / epoch (OLMo tokenizer; not the Qwen 32.4M count); endpoint **63,378,772** assistant tokens (2 epochs) | | Train seed | **42** | ## Recipe - LoRA **r64 / α128**, dropout 0.0, seven projections: `q_proj`, `k_proj`, `v_proj`, `o_proj`, `gate_proj`, `up_proj`, `down_proj` - Embeddings / `lm_head` frozen except **two-sided trainable B-row** for **100257** (`<|endoftext|>`). Token id from `adapter/TOKEN_ROWS_META.json`. - Assistant supervised tail: `<|endoftext|>` (**100257**) - LR **1e-4**, AdamW (β 0.9/0.95), **cosine** over assistant-token dose, **warmup 6%** (3,802,726 / 63,378,772 tokens), weight decay **0.1** - **bf16**, no packing, no truncation, context 32768 at train time - **2 epochs**, physical concat. Endpoint-only score; no checkpoint picking. - Chat template: `olmo3-lcb-noprefill` (no generation-prompt `` prefill). Bundled as `chat_template.jinja`. Merged weights are the 2-epoch endpoint (`step-000904`, 63,378,772 assistant tokens). LoRA + B-row are under `adapter/`. ## Evaluation (DEV256) 256-problem LiveCodeBench-derived **dev** split. Seed **3407**, **think** mode, **no `` prefill**, max generation ~32k, sandbox-verified **pass@1**. Temperature 0.6, top-p 0.95, top-k 20. **Cap** = generations that hit the 32k length limit without closing ``. | Model | pass@1 | Cap | Notes | |---|---:|---:|---| | **code-think-o7b-20260908** | **56/256** | **149** | this repo; seed 3407 | | Olmo-3-1025-7B (same contract, think) | 15/256 | 104 | bare base, seed 3407 | Single seed. These are research checkpoints, not product scores. ## Usage Merged full weights; no PEFT required at inference. The pinned OLMo template supplies a default system turn. **Do not** prefill ``. ```python from transformers import AutoModelForCausalLM, AutoTokenizer repo = "modrill/code-think-o7b-20260908" tokenizer = AutoTokenizer.from_pretrained(repo) model = AutoModelForCausalLM.from_pretrained( repo, torch_dtype="bfloat16", device_map="auto" ) messages = [{"role": "user", "content": problem_statement}] prompt = tokenizer.apply_chat_template( messages, tokenize=False, add_generation_prompt=True, ) inputs = tokenizer(prompt, return_tensors="pt").to(model.device) output = model.generate( **inputs, max_new_tokens=32768, do_sample=True, temperature=0.6, top_p=0.95, top_k=20, ) print(tokenizer.decode(output[0][inputs["input_ids"].shape[1]:], skip_special_tokens=False)) ``` Stop ids used in the official eval: `100257` (`<|endoftext|>`), `100265` (`<|im_end|>`). ## Repo layout - Root: merged HF weights (`config.json`, `model.safetensors`, tokenizer, `generation_config.json`, `chat_template.jinja`) plus `OFFICIAL_MERGE_RECEIPT.json` - `adapter/`: LoRA, `token_rows_both_sides.safetensors`, `TOKEN_ROWS_META.json`, checkpoint `MANIFEST.json` - `provenance/`: train `RUN_IDENTITY.json`, `TRAINING_CONFIG.json`, `POLICY.json`; DEV256 `COMPLETE.json` - `MANIFEST.sha256` Optimizer / resume states are **not** included.