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Model: IlyaGusev/saiga_llama3_8b
Source: Original Platform

.gitattributes

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README.md

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+---
+language:
+- ru
+datasets:
+- IlyaGusev/saiga_scored
+license: other
+license_name: llama3
+license_link: https://llama.meta.com/llama3/license/
+---
+
+
+# Saiga/Llama3 8B, Russian Llama-3-based chatbot
+
+Based on [Llama-3 8B Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct).
+
+Llama.cpp version: [link](https://huggingface.co/IlyaGusev/saiga_llama3_8b_gguf)
+
+Colab: [link](https://colab.research.google.com/drive/1qxgIPymzW6_H6s_wwXu3lknkkYM45Db4)
+
+## Prompt format
+
+**ОСТОРОЖНО! WARNING! LET OP!**
+
+I've changed the prompt format from ChatML to **the original Llama-3 format in v4**. Don't forget to switch formats!
+
+**v4, v5, v6+**: LLama-3 prompt format:
+```
+<|begin_of_text|><|start_header_id|>system<|end_header_id|>
+
+Ты — Сайга, русскоязычный автоматический ассистент. Ты разговариваешь с людьми и помогаешь им.<|eot_id|><|start_header_id|>user<|end_header_id|>
+
+Как дела?<|eot_id|><|start_header_id|>assistant<|end_header_id|>
+
+Отлично, а у тебя?<|eot_id|><|start_header_id|>user<|end_header_id|>
+
+Шикарно. Как пройти в библиотеку?<|eot_id|><|start_header_id|>assistant<|end_header_id|>
+
+```
+
+
+**v2, v3**: ChatML prompt format:
+```
+<|im_start|>system
+Ты — Сайга, русскоязычный автоматический ассистент. Ты разговариваешь с людьми и помогаешь им.<|im_end|>
+<|im_start|>user
+Как дела?<|im_end|>
+<|im_start|>assistant
+Отлично, а у тебя?<|im_end|>
+<|im_start|>user
+Шикарно. Как пройти в библиотеку?<|im_end|>
+<|im_start|>assistant
+```
+
+## 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_llama3_8b"
+DEFAULT_SYSTEM_PROMPT = "Ты — Сайга, русскоязычный автоматический ассистент. Ты разговариваешь с людьми и помогаешь им."
+
+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": "system",
+        "content": DEFAULT_SYSTEM_PROMPT
+    }, {
+        "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()}
+    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 выглядит зеленым из-за наличия в ней хлорофилла – пигмента, который помогает растениям поглощать солнечную энергию для процесса фотосинтеза.
+Хлорофилл поглощает световые лучи с длиной волны 400-500 нанометров (ближе к синему) и отражает лучи с длиной волны 600-700 нанометров (ближе к красному), что делает его видимым как зеленый цвет.
+Таким образом, зеленый цвет является результатом того, как хлорофилл взаимодействует со светом, обеспечивая растения необходимой энергии для роста и развития.
+```
+
+```
+User: Сочини длинный рассказ, обязательно упоминая следующие объекты. Дано: Таня, мяч
+Saiga: В небольшой деревушке под открытым небом жила девочка по имени Таня. Она была очень активной и любящей играть в различные виды спорта. Однажды, когда она прогуливалась по полям, увидела на земле лежащий мяч. Это был старый, но все еще пригодный для игры мячик.
+Таня сразу же решила взять его себе домой и показать своему другу Мише. Мишка тоже обожал футбол и всегда рад был бы провести время вместе со своими друзьями. Когда они вернулись домой, Таня показала ему найденный мячик и предложила сыграть в футбол.
+Мишка был счастлив, что у них появился новый мяч, и они сразу же начали готовиться к матчу. Они построили две команды и начали игру. Играли они до вечера, а потом решили сделать перерыв и приготовить ужин.
+После ужина они продолжили игру, теперь уже с большим энтузиазмом и страстью. В конце концов, победителем стала команда Тани, которая забила больше голов. Все закончилось веселым праздником и хорошими воспоминаниями о проведенном времени.
+На следующий день Таня и Миша решили пригласить своих других друзей на игру. Они собрали всех в одном месте и провели ещё один захватывающий матч. Этот день также стал незабываемым благодаря новому мячу, который принес так много радости и улыбок.
+Итак, этот маленький мяч, который Таня нашла на поле, стал не просто предметом для игр, но и символом дружбы и веселья между детьми. Он помог им создать незабываемые моменты и укрепил их отношения.
+```
+
+
+## Versions
+v7:
+- [17e1bcc9c6d3e31852a95a168f7d3778f395cd2a](https://huggingface.co/IlyaGusev/saiga_llama3_8b/commit/17e1bcc9c6d3e31852a95a168f7d3778f395cd2a)
+- Other name: saiga_llama3_8b_abliterated_sft_m11_d7_kto_m7_d7
+- SFT dataset config: [sft_d7.json](https://github.com/IlyaGusev/saiga/blob/main/configs/datasets/sft_d7.json)
+- SFT model config: [saiga_llama3_8b_sft_m11.json](https://github.com/IlyaGusev/saiga/blob/main/configs/models/saiga_llama3_8b_sft_m11.json)
+- KTO dataset config: [pref_d7.json](https://github.com/IlyaGusev/saiga/blob/main/configs/datasets/pref_d7.json)
+- KTO model config: [saiga_llama3_8b_kto_m7.json](https://github.com/IlyaGusev/saiga/blob/main/configs/models/saiga_llama3_8b_kto_m7.json)
+- SFT wandb: [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/2ympfu9y)
+- KTO wandb: [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/9zn4825e)
+
+v6:
+- [b662833f247ca04f1843b356e7ff3ee4aef8086a](https://huggingface.co/IlyaGusev/saiga_llama3_8b/commit/b662833f247ca04f1843b356e7ff3ee4aef8086a)
+- Other name: saiga_llama3_8b_sft_m10_d1_kto_m2_d2
+- SFT dataset config: [sft_d1.json](https://github.com/IlyaGusev/saiga/blob/main/configs/datasets/sft_d1.json)
+- SFT model config: [saiga_llama3_8b_sft_m10.json](https://github.com/IlyaGusev/saiga/blob/main/configs/models/saiga_llama3_8b_sft_m10.json)
+- KTO dataset config: [pref_d2.json](https://github.com/IlyaGusev/saiga/blob/main/configs/datasets/pref_d2.json)
+- KTO model config: [saiga_llama3_8b_kto_m2.json](https://github.com/IlyaGusev/saiga/blob/main/configs/models/saiga_llama3_8b_kto_m2.json)
+- SFT wandb: [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/0iepauzu)
+- KTO wandb: [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/s6l98eot)
+
+v5:
+- [d947b00c56683cd4b2f7ce707edef89318027be4](https://huggingface.co/IlyaGusev/saiga_llama3_8b/commit/d947b00c56683cd4b2f7ce707edef89318027be4)
+- KTO-tune over v4, dataset: [lmsys_clean_ru_preferences](https://huggingface.co/datasets/IlyaGusev/lmsys_clean_ru_preferences)
+- wandb [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/se1mbx7n)
+
+v4:
+- [1cc945d4ca2c7901cf989e7edaac52ab24f1a7dd](https://huggingface.co/IlyaGusev/saiga_llama3_8b/commit/1cc945d4ca2c7901cf989e7edaac52ab24f1a7dd)
+- dataset: [saiga_scored](https://huggingface.co/datasets/IlyaGusev/saiga_scored), scores >= 8, c66032920556c0f21bbbed05e7e04433ec954c3d
+- wandb [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/dcbs9ttt)
+
+v3:
+- [c588356cd60bdee54d52c2dd5a2445acca8aa5c3](https://huggingface.co/IlyaGusev/saiga_llama3_8b/commit/c588356cd60bdee54d52c2dd5a2445acca8aa5c3)
+- dataset: [saiga_scored](https://huggingface.co/datasets/IlyaGusev/saiga_scored), scores >= 8, d51cf8060bdc90023da8cf1c3f113f9193d6569b
+- wandb [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/ltoqdsal)
+
+v2:
+- [ae61b4f9b34fac9856d361ea78c66284a00e4f0b](https://huggingface.co/IlyaGusev/saiga_llama3_8b/commit/ae61b4f9b34fac9856d361ea78c66284a00e4f0b)
+- dataset code revision d0d123dd221e10bb2a3383bcb1c6e4efe1b4a28a
+- wandb [link](https://wandb.ai/ilyagusev/huggingface/runs/r6u5juyk)
+- 5 datasets: ru_turbo_saiga, ru_sharegpt_cleaned, oasst1_ru_main_branch, gpt_roleplay_realm, ru_instruct_gpt4
+- Datasets merging script: [create_short_chat_set.py](https://github.com/IlyaGusev/rulm/blob/d0d123dd221e10bb2a3383bcb1c6e4efe1b4a28a/self_instruct/src/data_processing/create_short_chat_set.py)
+
+
+## Evaluation
+
+* Dataset: https://github.com/IlyaGusev/rulm/blob/master/self_instruct/data/tasks.jsonl
+* Framework: https://github.com/tatsu-lab/alpaca_eval
+* Evaluator: alpaca_eval_cot_gpt4_turbo_fn
+
+Pivot: chatgpt_3_5_turbo
+| model | length_controlled_winrate |  win_rate | standard_error  | avg_length |
+|-----|-----|-----|-----|-----|
+|chatgpt_4_turbo | 76.04 | 90.00 |1.46 | 1270 |
+|chatgpt_3_5_turbo | 50.00 | 50.00 | 0.00  | 536 |
+|saiga_llama3_8b, v6 | 49.33 | 68.31 | 2.26  | 1262 |
+|sfr-iter-dpo | 49.11 | 74.94 | 2.13 | 1215 |
+|suzume | 49.05 | 71.57 | 2.20  | 1325 |
+|saiga_llama3_8b, v7| 48.95 | 69.40 | 2.25 | 1266 |
+|saiga_llama3_8b, v5  | 47.13  | 66.18 | 2.31 | 1194 |
+|saiga_llama3_8b, v4  | 43.64  | 65.90 | 2.31 | 1200 |
+|saiga_llama3_8b, v3  | 36.97  | 61.08 | 2.38 | 1162 |
+|saiga_llama3_8b, v2  | 33.07  | 48.19 | 2.45 | 1166 |
+|saiga_mistral_7b  | 23.38  | 35.99 | 2.34 | 949  |
+
+Pivot: sfr
+| model | length_controlled_winrate |  win_rate | standard_error  | avg_length |
+|-----|-----|-----|-----|-----|
+| sfr | 50.00 |  50.00 | 0.00 | 1215 |
+| saiga_llama3_8b, v7 |  48.95  |  49.16  | 2.46  | 1266 |
+| saiga_llama3_8b, v6 | 46.91 | 47.23 | 2.45 | 1262 |
+| suzume_8b | 43.69  | 48.19 | 2.46 | 1325 |

config.json

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+{
+  "_name_or_path": "models/llama-3-8b",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": 128001,
+  "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",
+  "use_cache": true,
+  "vocab_size": 128256
+}

generation_config.json

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+  "_from_model_config": true,
+  "bos_token_id": 128000,
+  "eos_token_id": 128009,
+  "pad_token_id": 128000,
+  "transformers_version": "4.34.0",
+  "temperature": 0.2,
+  "top_p": 0.9,
+  "top_k": 30,
+  "repetition_penalty": 1.12,
+  "do_sample": true,
+  "max_new_tokens": 1536
+}

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special_tokens_map.json

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