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Browse files- .gitattributes +1 -0
- README.md +167 -0
- cal_data.safetensors +3 -0
- config.json +29 -0
- generation_config.json +13 -0
- hidden_states.safetensors +3 -0
- job_new.json +0 -0
- measurement.json +0 -0
- model.safetensors.index.json +370 -0
- special_tokens_map.json +12 -0
- tokenizer.json +3 -0
- tokenizer_config.json +0 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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language:
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- ru
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datasets:
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- IlyaGusev/saiga_scored
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- IlyaGusev/saiga_preferences
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license: apache-2.0
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---
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# Saiga/MistralNemo 12B, Russian fine-tune of Mistral Nemo
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Based on [an abliterated version](https://huggingface.co/natong19/Mistral-Nemo-Instruct-2407-abliterated) of [Mistral Nemo](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407).
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Llama.cpp version: [link](https://huggingface.co/IlyaGusev/saiga_nemo_12b_gguf)
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Colab: [link](https://colab.research.google.com/drive/1vNzMyPqx2GB7zk3ANDtZEfvhzgYOWu0B)
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## Prompt format
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v3: Original Misral Nemo prompt format, but the system prompt is in the beginning:
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```
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<s>Ты — Сайга, русскоязычный автоматический ассистент. Ты разговариваешь с людьми и помогаешь им.
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[INST]Как дела?[/INST][INST]Шикарно. Как пройти в библиотеку?[/INST]
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```
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v1, v2: Original Misral Nemo prompt format, but the system prompt is in the beginning and there are additional spaces:
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```
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<s>Ты — Сайга, русскоязычный автоматический ассистент. Ты разговариваешь с людьми и помогаешь им.
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[INST] Как дела? [/INST] Отлично, а у тебя? </s>[INST] Шикарно. Как пройти в библиотеку? [/INST]
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```
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## Code example
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```python
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# Исключительно ознакомительный пример.
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# НЕ НАДО ТАК ИНФЕРИТЬ МОДЕЛЬ В ПРОДЕ.
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# См. https://github.com/vllm-project/vllm или https://github.com/huggingface/text-generation-inference
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
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MODEL_NAME = "IlyaGusev/saiga_nemo_12b"
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model = AutoModelForCausalLM.from_pretrained(
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MODEL_NAME,
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load_in_8bit=True,
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torch_dtype=torch.bfloat16,
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device_map="auto"
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)
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model.eval()
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tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
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generation_config = GenerationConfig.from_pretrained(MODEL_NAME)
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print(generation_config)
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inputs = ["Почему трава зеленая?", "Сочини длинный рассказ, обязательно упоминая следующие объекты. Дано: Таня, мяч"]
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for query in inputs:
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prompt = tokenizer.apply_chat_template([{
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"role": "user",
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"content": query
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}], tokenize=False, add_generation_prompt=True)
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data = tokenizer(prompt, return_tensors="pt", add_special_tokens=False)
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data = {k: v.to(model.device) for k, v in data.items()}
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data.pop("token_type_ids", None)
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output_ids = model.generate(**data, generation_config=generation_config)[0]
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output_ids = output_ids[len(data["input_ids"][0]):]
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output = tokenizer.decode(output_ids, skip_special_tokens=True).strip()
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print(query)
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print(output)
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print()
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print("==============================")
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print()
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```
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## Output examples
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```
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User: Почему трава зеленая?
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Saiga: Трава зеленая из-за содержания хлорофилла. Hлорофилл — это пигмент, основной компонент системы фотосинтеза в растениях (а также водорослях и некоторых бактериях). Функционирование хлорофилла обеспечивает следующие особенности:
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1. **Абсорбция света**: Хлорофилл поглощает свет в определенном диапазоне спектра, в основном синий и красный цвета. Зеленый цвет отражается обратно к нашему глазу, поскольку именно этот цвет не поглощается хлорофиллом.
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2. **Фотосинтез**: В процессе фотосинтеза хлорофилл преобразует энергию солнечного света в химическую энергию, необходимую для синтеза органических веществ (главным образом глюкозы) из углекислого газа и воды. Этот процесс поддерживает жизнь растений и является источником пищи для многих живых существ на Земле.
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3. **Структурная роль**: Хлорофилл расположен в особой структуре клеток растений – хлоропластах, которые играют ключевую роль в организации клетки.
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Таким образом, трава зеленая потому, что хлорофилл выполняет жизненно важную функцию в растении и отражает именно тот цвет света, который он не использует в своем процессе работы.
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```
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```
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User: Сочини длинный рассказ, обязательно упоминая следующие объекты. Дано: Таня, мяч
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Saiga: Таня и Мяч
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В далеком приморском городке, где ласковое солнце играло на волнах и свежий морской ветер наполнял воздух солью и свободой, жила девушка по имени Таня. Ее жизнь была полна ярких красок и незабываемых историй — и все благодаря одному простому предмету: мячу.
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Таня появилась в этом мире уже с мячом под мышкой. Ее отец, заядлый футбольный фанат, еще до рождения дочери решил, что она продолжит семейную спортивную традицию. И вот, когда маленькая Таня впервые сделала свои неуверенные шаги, в ее ручке оказался тот самый мяч — бледно-голубой, как небо над морем, с рисунком в виде волны, словно приглашая к приключениям.
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С тех пор мяч стал для Тани настоящим другом и спутником жизни. Они начинали каждое утро вместе: на песке у пляжа, где отпечатки ног смешивались с влажными линиями прилива; иногда на стадионе, где запахи травы и свежей росы сопровождали первые удары об мяч; а зимними днями — в просторном школьном коридоре, куда Таня выносила мяч, чтобы тренироваться прямо там, среди шумных перерывов и звонков.
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Мяч был свидетелем всех ключевых моментов ее жизни. Когда Таня в первый раз забила гол в школьной команде, он, казалось, излучал радость и гордость. Этот мяч побывал в каждом уголке города: они исследовали заброшенные склады, где Таня представляла себя героиней фильма о футболе; забрались на вершину старого маяка, откуда открывался вид на бескрайнее море; даже однажды ночью пытались пройти через весь город, запуская мяч от стены к стене, создавая свой собственный «марафон».
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Самый значительный эпизод их совместного пути произошел летом, когда Таня решила принять участие в региональных соревнованиях по футболу. Мяч, который уже успел потерять немного своей первоначальной гладкости и белизны, приобрел особое значение. Это был не просто мяч — это символ мечты, которую она носила внутри себя. В день финального матча Таня почувствовала, как каждый удар об этот мяч наполняет ее уверенностью и теплом воспоминаний. На последних минутах встречи, когда счет был равным, Таня ловко обвела соперниц и, сделав красивый финт, послала мяч точно в ворота противника. Зрители взорвались аплодисментами, а Таня упала на колени, крепко обнимая своего верного друга.
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После победы Таня поняла, что мяч стал частью её души. Его история переплеталась со всеми важными моментами её жизни. Она решила сохранить его таким, какой он есть — слегка потрепанным, но полным истории и воспоминаний. Таня повесила мяч на стену в своей комнате, рядом с фотографиями друзей, трофеев и других дорогих сердцу предметов. Теперь он смотрел на неё, напоминая о том, что путь к мечтам долгий, но каждая ступень этого пути полна смысла и радости.
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И хотя со временем Таня увлеклась другими аспектами жизни — путешестви��ми, учебой, новыми увлечениями — мяч всегда оставался напоминанием о том, как важно сохранять искренность намерений и верность своим мечтам. А иногда, поздними вечерами, когда в городе наступала тишина, Таня доставала мяч из коробки, где он хранился, и несколько минут просто крутила его в руках, возвращаясь в те золотые дни детства и юности, наполненные беззаботностью и радостью первого большого приключения.
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```
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## Versions
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v3:
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- [d4f395741d0d363665e86533b53d5a2ec14477eb](https://huggingface.co/IlyaGusev/saiga_nemo_12b/commit/d4f395741d0d363665e86533b53d5a2ec14477eb)
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- Other names: saiga_nemo_12b_sft_m10_d16_simpo_m23_d38
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- SFT dataset config: [sft_d16.json](https://github.com/IlyaGusev/saiga/blob/main/configs/datasets/sft_d16.json)
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- SFT model config: [saiga_nemo_12b_sft_m10.json](https://github.com/IlyaGusev/saiga/blob/main/configs/models/saiga_nemo_12b_sft_m10.json)
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- SimPO dataset config: [pref_d38.json](https://github.com/IlyaGusev/saiga/blob/main/configs/datasets/pref_d38.json)
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- SimPO model config: [saiga_nemo_12b_simpo_m23.json](https://github.com/IlyaGusev/saiga/blob/main/configs/models/saiga_nemo_12b_simpo_m23.json)
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- SFT wandb: [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/hzs68let)
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- SimPO wandb: [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/hyz52bom)
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v2:
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- [2ae4ce589c6c1c0ef3ba26521d78882ae1ae2930](https://huggingface.co/IlyaGusev/saiga_nemo_12b/commit/2ae4ce589c6c1c0ef3ba26521d78882ae1ae2930)
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- Other names: saiga_nemo_12b_sft_m9_d16_slerp, saiga_nemo_12b_sft_m9_d16_simpo_m21_d36_doestoevsky_orpo_m1_slerp
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- SFT dataset config: [sft_d16.json](https://github.com/IlyaGusev/saiga/blob/main/configs/datasets/sft_d16.json)
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- SFT model config: [saiga_nemo_12b_sft_m9.json](https://github.com/IlyaGusev/saiga/blob/main/configs/models/saiga_nemo_12b_sft_m9.json)
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- SimPO dataset config: [pref_d36.json](https://github.com/IlyaGusev/saiga/blob/main/configs/datasets/pref_d36.json)
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- SimPO model config: [saiga_nemo_12b_simpo_m21.json](https://github.com/IlyaGusev/saiga/blob/main/configs/models/saiga_nemo_12b_simpo_m21.json)
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- SFT wandb: [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/yod78hiq)
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- SimPO wandb: [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/bv5w0lxl)
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- Dostoevsky wandb: [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/senqj9t1)
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- Merge config: [link](https://huggingface.co/IlyaGusev/saiga_nemo_12b_sft_m9_d16_slerp/blob/main/mergekit_config.yml)
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v1:
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- [1c13507be4b5b5edd5586e48c902ef61c0343299](https://huggingface.co/IlyaGusev/saiga_nemo_12b/commit/1c13507be4b5b5edd5586e48c902ef61c0343299)
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- Other name: saiga_nemo_12b_sft_m9_d14_simpo_m19_d31
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- SFT dataset config: [sft_d14.json](https://github.com/IlyaGusev/saiga/blob/main/configs/datasets/sft_d14.json)
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- SFT model config: [saiga_nemo_12b_sft_m9.json](https://github.com/IlyaGusev/saiga/blob/main/configs/models/saiga_nemo_12b_sft_m9.json)
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- SimPO dataset config: [pref_d31.json](https://github.com/IlyaGusev/saiga/blob/main/configs/datasets/pref_d31.json)
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- SimPO model config: [saiga_nemo_12b_simpo_m19.json](https://github.com/IlyaGusev/saiga/blob/main/configs/models/saiga_nemo_12b_simpo_m19.json)
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- SFT wandb: [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/e74ozfzh)
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- SimPO wandb: [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/b094iiej)
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## Evaluation
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### v3:
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RuArenaHard:
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/5fc2346dea82dd667bb0ffbc/tTTHRqxwrLnhj7LEeFmsU.png)
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PingPong:
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/5fc2346dea82dd667bb0ffbc/4VxQJjAxw2eQMYctUvBr5.png)
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### v2
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RuArenaHard:
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/5fc2346dea82dd667bb0ffbc/dn5BAxdsYsMfO0oGYH2Zb.png)
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PingPong:
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/5fc2346dea82dd667bb0ffbc/tlxLQORAmGQpkJa6OeLBh.png)
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### v1
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RuArenaHard:
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tokenizer.json
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tokenizer_config.json
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