commit 673bcd8c2582929ccd2386b10fa78e76b9e02a3d
Author: ModelHub XC <noreply@modelhub.org.cn>
Date:   Sat May 23 19:49:12 2026 +0800

    初始化项目，由ModelHub XC社区提供模型
    
    Model: rinna/gemma-2-baku-2b-it
    Source: Original Platform

diff --git a/.gitattributes b/.gitattributes
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diff --git a/Notice b/Notice
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+Gemma is provided under and subject to the Gemma Terms of Use found at ai.google.dev/gemma/terms
diff --git a/README.md b/README.md
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+---
+thumbnail: https://github.com/rinnakk/japanese-pretrained-models/blob/master/rinna.png
+license: gemma
+language:
+- ja
+tags:
+- gemma2
+- conversational
+base_model:
+- google/gemma-2-2b
+- google/gemma-2-2b-it
+- rinna/gemma-2-baku-2b
+base_model_relation: merge
+pipeline_tag: text-generation
+library_name: transformers
+---
+
+
+# `Gemma 2 Baku 2B Instruct (rinna/gemma-2-baku-2b-it)`
+
+![rinna-icon](./rinna.png)
+
+# Overview
+
+The model is an instruction-tuned variant of [rinna/gemma-2-baku-2b](https://huggingface.co/rinna/gemma-2-baku-2b), utilizing Chat Vector and Odds Ratio Preference Optimization (ORPO) for fine-tuning. It adheres to the gemma-2 chat format.
+
+| Size | Continual Pre-Training | Instruction-Tuning |
+| :-   | :-                     | :-                 |
+| 2B   | Gemma 2 Baku 2B [[HF]](https://huggingface.co/rinna/gemma-2-baku-2b) | Gemma 2 Baku 2B Instruct [[HF]](https://huggingface.co/rinna/gemma-2-baku-2b-it) |
+
+* **Model architecture**
+
+    A 26-layer, 2304-hidden-size transformer-based language model. Please refer to the [Gemma 2 Model Card](https://www.kaggle.com/models/google/gemma-2/) for detailed information on the model's architecture.
+
+* **Training**
+
+    **Model merging.** The base model was endowed with instruction-following capabilities through a chat vector addition process. The chat vector was derived by subtracting the parameter vectors of [google/gemma-2-2b](https://huggingface.co/google/gemma-2-2b) from [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it), as follows. 
+
+    ~~~~text
+    rinna/gemma-2-baku-2b + 1.0 * (google/gemma-2-2b-it - google/gemma-2-2b)
+    ~~~~
+
+    During this process, the embedding layer was excluded during the subtraction and addition of parameter vectors.
+    
+    **ORPO** was applied using a subset of the following dataset to further refine the performance of the merged model.
+
+    - rinna's internal dataset
+  
+* **Contributors**
+
+    - [Xinqi Chen](https://huggingface.co/Keely0419)
+    - [Toshiaki Wakatsuki](https://huggingface.co/t-w)
+    - [Kei Sawada](https://huggingface.co/keisawada)
+
+* **Release date**
+
+    October 3, 2024
+
+---
+
+# Benchmarking
+
+Please refer to [rinna's LM benchmark page (Sheet 20241003)](https://rinnakk.github.io/research/benchmarks/lm/index.html).
+
+---
+
+# How to use the model
+
+~~~~python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_id = "rinna/gemma-2-baku-2b-it"
+dtype = torch.bfloat16
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    device_map="cuda",
+    torch_dtype=dtype,
+    attn_implementation="eager",
+)
+
+chat = [
+    { "role": "user", "content": "西田幾多郎とはどんな人物ですか？" },
+]
+prompt = tokenizer.apply_chat_template(chat, tokenize=False, add_generation_prompt=True)
+
+input_ids = tokenizer.encode(prompt, add_special_tokens=False, return_tensors="pt").to(model.device)
+outputs = model.generate(
+    input_ids,
+    max_new_tokens=512,
+)
+
+response = tokenizer.decode(outputs[0][input_ids.shape[-1]:], skip_special_tokens=True)
+print(response)
+~~~~
+
+It is recommended to use eager attention when conducting batch inference under bfloat16 precision. 
+Currently, Gemma 2 yields NaN values for input sequences with padding when the default attention mechanism (torch.scaled_dot_product_attention) is employed in conjunction with bfloat16.
+
+---
+
+# Tokenization
+The model uses the original [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it) tokenizer.
+
+---
+
+# How to cite
+```bibtex
+@misc{rinna-gemma-2-baku-2b-it,
+    title = {rinna/gemma-2-baku-2b-it},
+    author = {Chen, Xinqi and Wakatsuki, Toshiaki and Sawada, Kei},
+    url = {https://huggingface.co/rinna/gemma-2-baku-2b-it}
+}
+
+@inproceedings{sawada2024release,
+    title = {Release of Pre-Trained Models for the {J}apanese Language},
+    author = {Sawada, Kei and Zhao, Tianyu and Shing, Makoto and Mitsui, Kentaro and Kaga, Akio and Hono, Yukiya and Wakatsuki, Toshiaki and Mitsuda, Koh},
+    booktitle = {Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)},
+    month = {5},
+    year = {2024},
+    pages = {13898--13905},
+    url = {https://aclanthology.org/2024.lrec-main.1213},
+    note = {\url{https://arxiv.org/abs/2404.01657}}
+}
+```
+---
+
+# References
+```bibtex
+@article{gemma-2-2024,
+    title = {Gemma 2},
+    url = {https://www.kaggle.com/models/google/gemma-2},
+    publisher = {Kaggle},
+    author = {Gemma Team},
+    year = {2024}
+}
+
+@article{huang2023chat,
+    title = {Chat Vector: A Simple Approach to Equip LLMs with Instruction Following and Model Alignment in New Languages},
+    author = {Huang, Shih-Cheng and Li, Pin-Zu and Hsu, Yu-Chi and Chen, Kuang-Ming and Lin, Yu Tung and Hsiao, Shih-Kai and Tzong-Han Tsai, Richard and Lee, Hung-yi},
+    year = {2023},
+    url = {https://arxiv.org/abs/2310.04799}
+}
+
+@article{hong2024orpo,
+  title = {ORPO: Monolithic Preference Optimization without Reference Model},
+  author = {Hong, Jiwoo and Lee, Noah and Thorne, James},
+  year = {2024},
+  url = {https://arxiv.org/abs/2403.07691}
+}
+```
+---
+
+# License
+[Gemma Terms of Use](https://ai.google.dev/gemma/terms)
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+  ],
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+  "model_type": "gemma2",
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+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "torch_dtype": "float32",
+  "transformers_version": "4.44.0",
+  "use_cache": true,
+  "vocab_size": 256000
+}
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--- /dev/null
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@@ -0,0 +1,2013 @@
+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "added_tokens_decoder": {
+    "0": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
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+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
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+      "content": "[@BOS@]",
+      "lstrip": false,
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+      "single_word": false,
+      "special": false
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+    "198": {
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+    },
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+    "213": {
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+    "255968": {
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+    "255969": {
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+    "255993": {
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+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "255994": {
+      "content": "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
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+    },
+    "255995": {
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+      "normalized": false,
+      "rstrip": false,
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+    },
+    "255996": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "255997": {
+      "content": "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "255998": {
+      "content": "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "255999": {
+      "content": "<unused99>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_special_tokens": [
+    "<start_of_turn>",
+    "<end_of_turn>"
+  ],
+  "bos_token": "<bos>",
+  "chat_template": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '\n' + message['content'] | trim + '<end_of_turn>\n' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model\n'}}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<eos>",
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<pad>",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "GemmaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}