Instructions to use KakashiFromKonoha/ror-recite-27b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KakashiFromKonoha/ror-recite-27b with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("KakashiFromKonoha/ror-recite-27b") model = AutoModelForMultimodalLM.from_pretrained("KakashiFromKonoha/ror-recite-27b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
ror-recite-27b: the reciting 27B (candidate B)
One of the two specialists from Reason or Recite: Complementary Specialists with an LLM Judge for Traffic Anomaly Reasoning. This is the recite candidate: it drops the reasoning trace entirely and is trained on answers alone. Its counterpart, ror-recite-9b, reasons before answering, and a Qwen3.6-27B judge picks between the two per item.
Code, configs, and the full submission driver: https://github.com/mayur-ag/reason-or-recite
What this checkpoint is
- Base: Qwen/Qwen3.6-27B, with a rank-64 LoRA merged in. These are the merged weights, so no adapter loading is needed.
- Data: the TAR (Traffic Anomaly Reasoning) training set, answers only;
the adapter drops the reasoning field.
scene_descriptionandvideo_summarizationare fused into a single<scene>…</scene>\n<summary>…</summary>target, soscene_descriptionis excluded as a separate task. - Recipe: LoRA r=64, α=128, dropout 0.05 on the LM over an NF4-quantized base (vision tower kept in bf16); 2 epochs, AdamW 2e-4 on cosine with 3% warmup, 24 frames per clip. QLoRA is what fits the 27B run on a single GPU.
How it is used in the submission
Candidate B answers 880 test items via HF generate at batch size 1 (step 3
of the reproduction driver: the 80 scene_description items are covered by
the fused answer, which step 4 splits back into scene and summary and from
which mcq_openended is derived). The judge defaults to this candidate:
switching to the 9B requires a unanimous verdict across both candidate orders
plus a separate refutation pass.
hf download KakashiFromKonoha/ror-recite-27b --local-dir $REPRO_MODELS/qwen36-27b-recite-merged
Then follow the reproduction steps in the repo.
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Base model
Qwen/Qwen3.6-27B