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LICENSE

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+META LLAMA 3 COMMUNITY LICENSE AGREEMENT
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Notice

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+Meta Llama 3 is licensed under the Meta Llama 3 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved.

README.md

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 ---
+thumbnail: https://github.com/rinnakk/japanese-pretrained-models/blob/master/rinna.png
 license: llama3
+datasets:
+- CohereForAI/aya_dataset
+- kunishou/databricks-dolly-15k-ja
+- kunishou/HelpSteer-35k-ja
+- kunishou/HelpSteer2-20k-ja
+- kunishou/hh-rlhf-49k-ja
+- kunishou/oasst1-chat-44k-ja
+- kunishou/oasst2-chat-68k-ja
+- meta-math/MetaMathQA
+- OpenAssistant/oasst1
+- OpenAssistant/oasst2
+- sahil2801/CodeAlpaca-20k
+language:
+- ja
+- en
+tags:
+- llama
+- llama-3
+inference: false
 ---
+
+# `Llama 3 Youko 8B Instruct (rinna/llama-3-youko-8b-instruct)`
+
+![rinna-icon](./rinna.png)
+
+# Overview
+
+The model is the instruction-tuned version of [rinna/llama-3-youko-8b](https://huggingface.co/rinna/llama-3-youko-8b), using supervised fine-tuning (SFT), Chat Vector, and direct preference optimization (DPO). It adpots the Llama-3 chat format.
+
+| Size | Continual Pre-Training | Instruction-Tuning |
+| :-   | :-                     | :-                 |
+| 8B   | Llama 3 Youko 8B [[HF]](https://huggingface.co/rinna/llama-3-youko-8b) [[GPTQ]](https://huggingface.co/rinna/llama-3-youko-8b-gptq) | Llama 3 Youko 8B Instruct [[HF]](https://huggingface.co/rinna/llama-3-youko-8b-instruct) [[GPTQ]](https://huggingface.co/rinna/llama-3-youko-8b-instruct-gptq) |
+| 70B  | Llama 3 Youko 70B [[HF]](https://huggingface.co/rinna/llama-3-youko-70b) [[GPTQ]](https://huggingface.co/rinna/llama-3-youko-70b-gptq) | Llama 3 Youko 70B Instruct [[HF]](https://huggingface.co/rinna/llama-3-youko-70b-instruct) [[GPTQ]](https://huggingface.co/rinna/llama-3-youko-70b-instruct-gptq) |
+
+* **Model architecture**
+
+    A 32-layer, 4096-hidden-size transformer-based language model. Refer to the [Llama 3 Model Card](https://github.com/meta-llama/llama3/blob/main/MODEL_CARD.md) for architecture details.
+
+* **Training: Built with Meta Llama 3**
+
+    **Supervised fine-tuning.** The supervised fine-tuning data is a subset of the following datasets.
+
+    - [CohereForAI/aya_dataset](https://huggingface.co/datasets/CohereForAI/aya_dataset)
+      - The JPN subset was used.
+    - [FLAN](https://github.com/google-research/FLAN/tree/main/flan/v2)
+    - [kunishou/databricks-dolly-15k-ja](https://huggingface.co/datasets/kunishou/databricks-dolly-15k-ja)
+    - [kunishou/hh-rlhf-49k-ja](https://huggingface.co/datasets/kunishou/hh-rlhf-49k-ja)
+    - [kunishou/oasst1-chat-44k-ja](https://huggingface.co/datasets/kunishou/oasst1-chat-44k-ja)
+    - [kunishou/oasst2-chat-68k-ja](https://huggingface.co/datasets/kunishou/oasst2-chat-68k-ja)
+    - [meta-math/MetaMathQA](https://huggingface.co/datasets/meta-math/MetaMathQA)
+      - The following sections were used: MATH_AnsAug, MATH_Rephrased, MATH_SV, and MATH_FOBAR.
+      - The remaining sections, containing augmented data from commonly used evaluation corpora, were skipped for preventing any possibility of data leak.
+    - [OpenAssistant/oasst1](https://huggingface.co/datasets/OpenAssistant/oasst1)
+      - The EN and JA subsets were used.
+    - [OpenAssistant/oasst2](https://huggingface.co/datasets/OpenAssistant/oasst2)
+      - The EN and JA subsets were used.
+    - [sahil2801/CodeAlpaca-20k](https://huggingface.co/datasets/sahil2801/CodeAlpaca-20k)
+    - rinna Dataset
+
+    **Model merging.** The fine-tuned model (llama-3-youko-8b-sft) has been enhanced through the following chat vector addition. The chat vector was obtained by subtracting the parameter vectors of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) from those of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct). 
+
+    ~~~~text
+    llama-3-youko-8b-sft + 0.5 * (meta-llama/Meta-Llama-3-8B-Instruct - meta-llama/Meta-Llama-3-8B)
+    ~~~~
+
+    Here, the embedding layer was skipped while subtracting and adding the parameter vectors.
+    
+    **Direct preference optimization**  was then applied with a subset of the following datasets to build this instruct model.
+
+    - [kunishou/HelpSteer-35k-ja](https://huggingface.co/datasets/kunishou/HelpSteer-35k-ja)
+    - [kunishou/HelpSteer2-20k-ja](https://huggingface.co/datasets/kunishou/HelpSteer2-20k-ja)
+    - rinna Dataset
+  
+* **Contributors**
+
+    - [Xinqi Chen](https://huggingface.co/Keely0419)
+    - [Koh Mitsuda](https://huggingface.co/mitsu-koh)
+    - [Toshiaki Wakatsuki](https://huggingface.co/t-w)
+    - [Kei Sawada](https://huggingface.co/keisawada)
+
+---
+
+# Benchmarking
+
+Please refer to [rinna's LM benchmark page](https://rinnakk.github.io/research/benchmarks/lm/index.html).
+
+---
+
+# How to use the model
+
+We found this instruction-tuned model tends to generate repeated text more often than its base counterpart, and thus we set repetition_penalty=1.1 for better generation performance. The same repetition penalty was applied to the instruction-tuned model in the aforementioned evaluation experiments.
+
+~~~~python
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model_id = "rinna/llama-3-youko-8b-instruct"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+	model_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+
+messages = [
+    {"role": "system", "content": "あなたは誠実で優秀なアシスタントです。どうか、簡潔かつ正直に答えてください。"},
+    {"role": "user", "content": "西田幾多郎とはどんな人物ですか？"},
+]
+
+input_ids = tokenizer.apply_chat_template(
+	messages,
+    add_generation_prompt=True,
+    return_tensors="pt"
+).to(model.device)
+
+terminators = [
+	tokenizer.convert_tokens_to_ids("<|end_of_text|>"),
+    tokenizer.convert_tokens_to_ids("<|eot_id|>")
+]
+
+outputs = model.generate(
+	input_ids,
+    max_new_tokens=512,
+    eos_token_id=terminators,
+    do_sample=True,
+    temperature=0.6,
+    top_p=0.9,
+    repetition_penalty=1.1,
+)
+    
+response = outputs[0][input_ids.shape[-1]:]
+response = tokenizer.decode(response, skip_special_tokens=True)
+print(response)
+~~~~
+
+---
+
+# Tokenization
+The model uses the original [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) tokenizer.
+
+---
+
+# How to cite
+```bibtex
+@misc{rinna-llama-3-youko-8b-instruct,
+    title = {rinna/llama-3-youko-8b-instruct},
+    author = {Chen, Xinqi and Mitsuda, Koh and Wakatsuki, Toshiaki and Sawada, Kei},
+    url = {https://huggingface.co/rinna/llama-3-youko-8b-instruct}
+}
+
+@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{llama3modelcard,
+    title = {Llama 3 Model Card},
+    author = {AI@Meta},
+    year = {2024},
+    url = {https://github.com/meta-llama/llama3/blob/main/MODEL_CARD.md}
+}
+
+@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}
+}
+```
+---
+
+# License
+[Meta Llama 3 Community License](https://llama.meta.com/llama3/license/)

USE_POLICY.md

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+# Meta Llama 3 Acceptable Use Policy
+
+Meta is committed to promoting safe and fair use of its tools and features, including Meta Llama 3. If you
+access or use Meta Llama 3, you agree to this Acceptable Use Policy (“Policy”). The most recent copy of
+this policy can be found at [https://llama.meta.com/llama3/use-policy](https://llama.meta.com/llama3/use-policy)
+
+## Prohibited Uses
+
+We want everyone to use Meta Llama 3 safely and responsibly. You agree you will not use, or allow
+others to use, Meta Llama 3 to:
+
+1. Violate the law or others’ rights, including to:
+    1. Engage in, promote, generate, contribute to, encourage, plan, incite, or further illegal or unlawful activity or content, such as:
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+        5. Sexual solicitation
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+
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+    2. Guns and illegal weapons (including weapon development)
+    3. Illegal drugs and regulated/controlled substances
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+
+3. Intentionally deceive or mislead others, including use of Meta Llama 3 related to the following:
+    1. Generating, promoting, or furthering fraud or the creation or promotion of disinformation
+    2. Generating, promoting, or furthering defamatory content, including the creation of defamatory statements, images, or other content
+    3. Generating, promoting, or further distributing spam
+    4. Impersonating another individual without consent, authorization, or legal right
+    5. Representing that the use of Meta Llama 3 or outputs are human-generated
+    6. Generating or facilitating false online engagement, including fake reviews and other means of fake online engagement
+
+4. Fail to appropriately disclose to end users any known dangers of your AI system
+
+Please report any violation of this Policy, software “bug,” or other problems that could lead to a violation
+of this Policy through one of the following means:
+
+● Reporting issues with the model: [https://github.com/meta-llama/llama3](https://github.com/meta-llama/llama3)
+● Reporting risky content generated by the model:
+developers.facebook.com/llama_output_feedback
+● Reporting bugs and security concerns: facebook.com/whitehat/info
+● Reporting violations of the Acceptable Use Policy or unlicensed uses of Meta Llama 3:
+LlamaUseReport@meta.com

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": 128009,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 8192,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.40.0.dev0",
+  "use_cache": true,
+  "vocab_size": 128256
+}

generation_config.json

@@ -0,0 +1,10 @@
+{
+  "bos_token_id": 128000,
+  "eos_token_id": [128001, 128009],
+  "do_sample": true,
+  "temperature": 0.6,
+  "max_length": 4096,
+  "top_p": 0.9,
+  "repetition_penalty": 1.1,
+  "transformers_version": "4.40.0.dev0"
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:afb03252b7ab35bdbace3e1678a0c322443a1448532640a338daf656fdf89118
+size 16060556584

special_tokens_map.json

@@ -0,0 +1,4 @@
+{
+  "bos_token": "<|begin_of_text|>",
+  "eos_token": "<|end_of_text|>"
+}

tokenizer_config.json

@@ -0,0 +1,2062 @@
+{
+  "added_tokens_decoder": {
+    "128000": {
+      "content": "<|begin_of_text|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128001": {
+      "content": "<|end_of_text|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128002": {
+      "content": "<|reserved_special_token_0|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128003": {
+      "content": "<|reserved_special_token_1|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128004": {
+      "content": "<|reserved_special_token_2|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128005": {
+      "content": "<|reserved_special_token_3|>",
+      "lstrip": false,
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+      "single_word": false,
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+    },
+    "128006": {
+      "content": "<|start_header_id|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128007": {
+      "content": "<|end_header_id|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128008": {
+      "content": "<|reserved_special_token_4|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128009": {
+      "content": "<|eot_id|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
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+    "128011": {
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+      "lstrip": false,
+      "normalized": false,
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
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+      "content": "<|reserved_special_token_208|>",
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+    },
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+      "normalized": false,
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+      "single_word": false,
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+    },
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+      "single_word": false,
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+    },
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+      "content": "<|reserved_special_token_211|>",
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+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128217": {
+      "content": "<|reserved_special_token_212|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
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+    },
+    "128218": {
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+      "single_word": false,
+      "special": true
+    },
+    "128219": {
+      "content": "<|reserved_special_token_214|>",
+      "lstrip": false,
+      "normalized": false,
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+      "single_word": false,
+      "special": true
+    },
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+      "content": "<|reserved_special_token_215|>",
+      "lstrip": false,
+      "normalized": false,
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+      "single_word": false,
+      "special": true
+    },
+    "128221": {
+      "content": "<|reserved_special_token_216|>",
+      "lstrip": false,
+      "normalized": false,
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+      "single_word": false,
+      "special": true
+    },
+    "128222": {
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+    },
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+      "single_word": false,
+      "special": true
+    },
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+    },
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+    },
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+    },
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+    },
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+    },
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+      "single_word": false,
+      "special": true
+    },
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+      "content": "<|reserved_special_token_225|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128231": {
+      "content": "<|reserved_special_token_226|>",
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+      "single_word": false,
+      "special": true
+    },
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128233": {
+      "content": "<|reserved_special_token_228|>",
+      "lstrip": false,
+      "normalized": false,
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+      "single_word": false,
+      "special": true
+    },
+    "128234": {
+      "content": "<|reserved_special_token_229|>",
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+      "normalized": false,
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+      "single_word": false,
+      "special": true
+    },
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+      "special": true
+    },
+    "128236": {
+      "content": "<|reserved_special_token_231|>",
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+      "special": true
+    },
+    "128237": {
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+      "single_word": false,
+      "special": true
+    },
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+    },
+    "128239": {
+      "content": "<|reserved_special_token_234|>",
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+      "normalized": false,
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+      "single_word": false,
+      "special": true
+    },
+    "128240": {
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+      "single_word": false,
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+    },
+    "128241": {
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+      "special": true
+    },
+    "128242": {
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+      "special": true
+    },
+    "128243": {
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+      "single_word": false,
+      "special": true
+    },
+    "128244": {
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+      "lstrip": false,
+      "normalized": false,
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+      "special": true
+    },
+    "128245": {
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+      "single_word": false,
+      "special": true
+    },
+    "128246": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128247": {
+      "content": "<|reserved_special_token_242|>",
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+      "normalized": false,
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+      "single_word": false,
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+    },
+    "128248": {
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+      "single_word": false,
+      "special": true
+    },
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+      "special": true
+    },
+    "128250": {
+      "content": "<|reserved_special_token_245|>",
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+      "normalized": false,
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+      "single_word": false,
+      "special": true
+    },
+    "128251": {
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+      "normalized": false,
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+      "single_word": false,
+      "special": true
+    },
+    "128252": {
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+      "normalized": false,
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+      "single_word": false,
+      "special": true
+    },
+    "128253": {
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+      "lstrip": false,
+      "normalized": false,
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+      "special": true
+    },
+    "128254": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<|begin_of_text|>",
+  "chat_template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>\n\n' }}{% endif %}",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|eot_id|>",
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 1000000000000000019884624838656,
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}