Add LoRA adapter and model card

README.md

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+---
+base_model: jvonrad/olmo-2-7b-finetranslations
+library_name: peft
+pipeline_tag: text-generation
+license: apache-2.0
+tags:
+- lora
+- peft
+- multilingual
+- cross-lingual-consistency
+- base_model:adapter:jvonrad/olmo-2-7b-finetranslations
+datasets:
+- jvonrad/PolyFact-Clean
+language: [en, de, es, fr, pt, id, ru, zh, ar, ja, sw, bn]
+---
+
+# OLMo-2-7B-CPT-SFT-10k
+
+The same SFT recipe, applied on top of the translation-CPT checkpoint.
+
+A LoRA adapter (r=64, alpha=128) over
+[`jvonrad/olmo-2-7b-finetranslations`](https://huggingface.co/jvonrad/olmo-2-7b-finetranslations), trained for the paper
+*Improving Cross-Lingual Factual Recall via Consistency-Driven Reinforcement
+Learning*. It is one arm of a controlled comparison in which SFT, DCO, CM-Align
+and GRPO all see the **same 10,000 facts** from
+[`jvonrad/PolyFact-Clean`](https://huggingface.co/datasets/jvonrad/PolyFact-Clean)
+across the same 12 languages, so the methods differ only in objective.
+
+## Evaluation
+
+Accuracy (%) unless noted. PolyFact-Clean is the 2,039-fact curated test split
+with byte-normalised log-likelihood scoring; TotCons is the fraction of facts
+answered correctly in **all 12** languages; RankC is RankC@4 (floor 9.02,
+chance 37.68). KLAR is free-form generation over 17 languages, split into the
+7 seen in training and the 10 held out.
+
+| Model | PolyFact | TotCons | RankC | BMLAMA-53 | G-MMLU-Lite | KLAR seen | KLAR held-out |
+|---|---|---|---|---|---|---|---|
+| Base (`jvonrad/olmo-2-7b-finetranslations`) | 44.37 | 2.80 | 58.56 | 17.49 | 42.75 | 17.02 | 8.32 |
+| **This model** | 50.02 | 2.84 | 58.34 | 18.17 | 43.48 | 15.57 | 7.75 |
+
+## Usage
+
+```python
+from peft import PeftModel
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+base = AutoModelForCausalLM.from_pretrained("jvonrad/olmo-2-7b-finetranslations", dtype="bfloat16",
+                                            device_map="auto")
+model = PeftModel.from_pretrained(base, "jvonrad/OLMo-2-7B-CPT-SFT-10k")
+tok = AutoTokenizer.from_pretrained("jvonrad/OLMo-2-7B-CPT-SFT-10k")
+```
+
+Evaluation used the closed-book prompt `Question: {q}\nAnswer:` with the
+options hidden, matching `evaluate/evaluate_crosslingual_consistency.py`.
+
+## Citation
+
+```bibtex
+@misc{polyfact2026,
+  title  = {Improving Cross-Lingual Factual Recall via Consistency-Driven
+            Reinforcement Learning},
+  author = {von Rad, Jonathan},
+  year   = {2026},
+  eprint = {2606.06586},
+  archivePrefix = {arXiv}
+}
+```

adapter_config.json

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+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "jvonrad/olmo-2-7b-finetranslations",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 128,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "lora_ga_config": null,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "monteclora_config": null,
+  "peft_type": "LORA",
+  "peft_version": "0.20.0",
+  "qalora_group_size": 16,
+  "r": 64,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "k_proj",
+    "v_proj",
+    "o_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false,
+  "velora_config": null
+}

adapter_model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:4619b3f48534cf2ea972e4b152ff3b467b02c59596788f6bc7e883c45043aa5b
+size 268470272

tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": "<|endoftext|>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|endoftext|>",
+  "is_local": false,
+  "local_files_only": false,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<|pad|>",
+  "tokenizer_class": "TokenizersBackend",
+  "unk_token": "<|endoftext|>"
+}