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Model: IlyaGusev/saiga_nemo_12b
Source: Original Platform

.gitattributes

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README.md

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+---
+language:
+- ru
+datasets:
+- IlyaGusev/saiga_scored
+- IlyaGusev/saiga_preferences
+license: apache-2.0
+---
+
+
+# Saiga/MistralNemo 12B, Russian fine-tune of Mistral Nemo
+
+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).
+
+Llama.cpp version: [link](https://huggingface.co/IlyaGusev/saiga_nemo_12b_gguf)
+
+Colab: [link](https://colab.research.google.com/drive/1vNzMyPqx2GB7zk3ANDtZEfvhzgYOWu0B)
+
+## Prompt format
+
+v3: Original Misral Nemo prompt format, but the system prompt is in the beginning:
+```
+<s>Ты — Сайга, русскоязычный автоматический ассистент. Ты разговариваешь с людьми и помогаешь им.
+
+[INST]Как дела?[/INST]Отлично, а у тебя?</s>[INST]Шикарно. Как пройти в библиотеку?[/INST]
+```
+
+v1, v2: Original Misral Nemo prompt format, but the system prompt is in the beginning and there are additional spaces:
+```
+<s>Ты — Сайга, русскоязычный автоматический ассистент. Ты разговариваешь с людьми и помогаешь им.
+
+[INST] Как дела? [/INST] Отлично, а у тебя? </s>[INST] Шикарно. Как пройти в библиотеку? [/INST]
+```
+
+## Code example
+```python
+# Исключительно ознакомительный пример.
+# НЕ НАДО ТАК ИНФЕРИТЬ МОДЕЛЬ В ПРОДЕ.
+# См. https://github.com/vllm-project/vllm или https://github.com/huggingface/text-generation-inference
+
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
+
+MODEL_NAME = "IlyaGusev/saiga_nemo_12b"
+
+model = AutoModelForCausalLM.from_pretrained(
+    MODEL_NAME,
+    load_in_8bit=True,
+    torch_dtype=torch.bfloat16,
+    device_map="auto"
+)
+model.eval()
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+generation_config = GenerationConfig.from_pretrained(MODEL_NAME)
+print(generation_config)
+
+inputs = ["Почему трава зеленая?", "Сочини длинный рассказ, обязательно упоминая следующие объекты. Дано: Таня, мяч"]
+for query in inputs:
+    prompt = tokenizer.apply_chat_template([{
+        "role": "user",
+        "content": query
+    }], tokenize=False, add_generation_prompt=True)
+    data = tokenizer(prompt, return_tensors="pt", add_special_tokens=False)
+    data = {k: v.to(model.device) for k, v in data.items()}
+    data.pop("token_type_ids", None)
+    output_ids = model.generate(**data, generation_config=generation_config)[0]
+    output_ids = output_ids[len(data["input_ids"][0]):]
+    output = tokenizer.decode(output_ids, skip_special_tokens=True).strip()
+    print(query)
+    print(output)
+    print()
+    print("==============================")
+    print()
+```
+
+## Output examples
+```
+User: Почему трава зеленая?
+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:
+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.
+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.
+3. **Структурная роль**: Хлорофилл расположен в особой структуре клеток растений – хлоропластах, которые играют ключевую роль в организации клетки.
+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.
+```
+
+```
+User: Сочини длинный рассказ, обязательно упоминая следующие объекты. Дано: Таня, мяч
+Saiga: Таня и Мяч
+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.
+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.
+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.
+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».
+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.
+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.
+И хотя со временем Таня увлеклась другими аспектами жизни — путешествиями, 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.
+```
+
+
+## Versions
+
+v3:
+ - [d4f395741d0d363665e86533b53d5a2ec14477eb](https://huggingface.co/IlyaGusev/saiga_nemo_12b/commit/d4f395741d0d363665e86533b53d5a2ec14477eb)
+ - Other names: saiga_nemo_12b_sft_m10_d16_simpo_m23_d38
+ - SFT dataset config: [sft_d16.json](https://github.com/IlyaGusev/saiga/blob/main/configs/datasets/sft_d16.json)
+ - SFT model config: [saiga_nemo_12b_sft_m10.json](https://github.com/IlyaGusev/saiga/blob/main/configs/models/saiga_nemo_12b_sft_m10.json)
+ - SimPO dataset config: [pref_d38.json](https://github.com/IlyaGusev/saiga/blob/main/configs/datasets/pref_d38.json)
+ - SimPO model config: [saiga_nemo_12b_simpo_m23.json](https://github.com/IlyaGusev/saiga/blob/main/configs/models/saiga_nemo_12b_simpo_m23.json)
+ - SFT wandb: [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/hzs68let)
+ - SimPO wandb: [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/hyz52bom)
+
+v2:
+- [2ae4ce589c6c1c0ef3ba26521d78882ae1ae2930](https://huggingface.co/IlyaGusev/saiga_nemo_12b/commit/2ae4ce589c6c1c0ef3ba26521d78882ae1ae2930)
+- Other names: saiga_nemo_12b_sft_m9_d16_slerp, saiga_nemo_12b_sft_m9_d16_simpo_m21_d36_doestoevsky_orpo_m1_slerp
+- SFT dataset config: [sft_d16.json](https://github.com/IlyaGusev/saiga/blob/main/configs/datasets/sft_d16.json)
+- SFT model config: [saiga_nemo_12b_sft_m9.json](https://github.com/IlyaGusev/saiga/blob/main/configs/models/saiga_nemo_12b_sft_m9.json)
+- SimPO dataset config: [pref_d36.json](https://github.com/IlyaGusev/saiga/blob/main/configs/datasets/pref_d36.json)
+- SimPO model config: [saiga_nemo_12b_simpo_m21.json](https://github.com/IlyaGusev/saiga/blob/main/configs/models/saiga_nemo_12b_simpo_m21.json)
+- SFT wandb: [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/yod78hiq)
+- SimPO wandb: [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/bv5w0lxl)
+- Dostoevsky wandb: [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/senqj9t1)
+- Merge config: [link](https://huggingface.co/IlyaGusev/saiga_nemo_12b_sft_m9_d16_slerp/blob/main/mergekit_config.yml)
+
+v1:
+- [1c13507be4b5b5edd5586e48c902ef61c0343299](https://huggingface.co/IlyaGusev/saiga_nemo_12b/commit/1c13507be4b5b5edd5586e48c902ef61c0343299)
+- Other name: saiga_nemo_12b_sft_m9_d14_simpo_m19_d31
+- SFT dataset config: [sft_d14.json](https://github.com/IlyaGusev/saiga/blob/main/configs/datasets/sft_d14.json)
+- SFT model config: [saiga_nemo_12b_sft_m9.json](https://github.com/IlyaGusev/saiga/blob/main/configs/models/saiga_nemo_12b_sft_m9.json)
+- SimPO dataset config: [pref_d31.json](https://github.com/IlyaGusev/saiga/blob/main/configs/datasets/pref_d31.json)
+- SimPO model config: [saiga_nemo_12b_simpo_m19.json](https://github.com/IlyaGusev/saiga/blob/main/configs/models/saiga_nemo_12b_simpo_m19.json)
+- SFT wandb: [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/e74ozfzh)
+- SimPO wandb: [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/b094iiej)
+
+
+## Evaluation
+
+### v3:
+
+RuArenaHard:
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/5fc2346dea82dd667bb0ffbc/tTTHRqxwrLnhj7LEeFmsU.png)
+
+PingPong:
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/5fc2346dea82dd667bb0ffbc/4VxQJjAxw2eQMYctUvBr5.png)
+
+### v2
+
+RuArenaHard:
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/5fc2346dea82dd667bb0ffbc/dn5BAxdsYsMfO0oGYH2Zb.png)
+
+PingPong:
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/5fc2346dea82dd667bb0ffbc/tlxLQORAmGQpkJa6OeLBh.png)
+
+### v1
+
+RuArenaHard:
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/5fc2346dea82dd667bb0ffbc/-uG--3Wu9oUi9_bC_ZFP4.png)
+
+
+PingPong:
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/5fc2346dea82dd667bb0ffbc/uNmD2YhealySO6UYUH8-g.png)
+

config.json

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+{
+  "_name_or_path": "models/saiga_nemo_12b_sft_m10_d16",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 5120,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 1024000,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 40,
+  "num_key_value_heads": 8,
+  "pad_token_id": 10,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 1000000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.46.2",
+  "unsloth_version": "2024.8",
+  "use_cache": true,
+  "vocab_size": 131072
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "pad_token_id": 10,
+  "max_length": 1024000,
+  "max_new_tokens": 2048,
+  "temperature": 0.6,
+  "top_p": 0.95,
+  "repetition_penalty": 1.1,
+  "do_sample": true,
+  "transformers_version": "4.45.1"
+}

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