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--- |
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datasets: |
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- IlyaGusev/ru_turbo_saiga |
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- IlyaGusev/ru_sharegpt_cleaned |
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- IlyaGusev/oasst1_ru_main_branch |
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- IlyaGusev/ru_turbo_alpaca_evol_instruct |
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- lksy/ru_instruct_gpt4 |
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language: |
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- ru |
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pipeline_tag: conversational |
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license: cc-by-4.0 |
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--- |
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# Saiga/Mistral 7B, Russian Mistral-based chatbot |
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Based on [Mistral OpenOrca](https://huggingface.co/Open-Orca/Mistral-7B-OpenOrca). |
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This is an adapter-only version. |
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Llama.cpp version: TBA |
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Colab: TBA |
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Training code: [link](https://github.com/IlyaGusev/rulm/tree/master/self_instruct). |
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```python |
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from peft import PeftModel, PeftConfig |
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from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig |
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MODEL_NAME = "IlyaGusev/saiga_mistral_7b" |
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DEFAULT_MESSAGE_TEMPLATE = "<s>{role}\n{content}</s>" |
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DEFAULT_RESPONSE_TEMPLATE = "<s>bot\n" |
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DEFAULT_SYSTEM_PROMPT = "Ты — Сайга, русскоязычный автоматический ассистент. Ты разговариваешь с людьми и помогаешь им." |
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class Conversation: |
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def __init__( |
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self, |
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message_template=DEFAULT_MESSAGE_TEMPLATE, |
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system_prompt=DEFAULT_SYSTEM_PROMPT, |
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response_template=DEFAULT_RESPONSE_TEMPLATE |
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): |
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self.message_template = message_template |
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self.response_template = response_template |
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self.messages = [{ |
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"role": "system", |
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"content": system_prompt |
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}] |
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def add_user_message(self, message): |
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self.messages.append({ |
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"role": "user", |
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"content": message |
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}) |
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def add_bot_message(self, message): |
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self.messages.append({ |
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"role": "bot", |
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"content": message |
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}) |
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def get_prompt(self, tokenizer): |
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final_text = "" |
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for message in self.messages: |
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message_text = self.message_template.format(**message) |
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final_text += message_text |
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final_text += DEFAULT_RESPONSE_TEMPLATE |
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return final_text.strip() |
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def generate(model, tokenizer, prompt, generation_config): |
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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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output_ids = model.generate( |
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**data, |
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generation_config=generation_config |
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)[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) |
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return output.strip() |
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config = PeftConfig.from_pretrained(MODEL_NAME) |
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model = AutoModelForCausalLM.from_pretrained( |
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config.base_model_name_or_path, |
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load_in_8bit=True, |
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torch_dtype=torch.float16, |
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device_map="auto" |
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) |
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model = PeftModel.from_pretrained( |
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model, |
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MODEL_NAME, |
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torch_dtype=torch.float16 |
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) |
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model.eval() |
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tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, use_fast=False) |
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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 inp in inputs: |
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conversation = Conversation() |
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conversation.add_user_message(inp) |
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prompt = conversation.get_prompt(tokenizer) |
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output = generate(model, tokenizer, prompt, generation_config) |
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print(inp) |
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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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Examples: |
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``` |
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User: Почему трава зеленая? |
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Saiga: |
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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: |
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``` |
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v1: |
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- dataset code revision d0d123dd221e10bb2a3383bcb1c6e4efe1b4a28a |
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- wandb [link](https://wandb.ai/ilyagusev/rulm_self_instruct/runs/ip1qmm9p) |
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- 5 datasets: ru_turbo_saiga, ru_sharegpt_cleaned, oasst1_ru_main_branch, gpt_roleplay_realm, ru_instruct_gpt4 |
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- 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) |
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- saiga_mistral_7b vs saiga2_13b: 243-31-141 |
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