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README.md
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license: mit
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---
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license: mit
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---
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# FINGU-AI/Qwen2.5-7B-M
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## Overview
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`FINGU-AI/Qwen2.5-7B-M` is a powerful causal language model designed for a variety of natural language processing (NLP) tasks, including machine translation, text generation, and chat-based applications. This model is particularly useful for translating between Korean and Uzbek, as well as supporting other custom NLP tasks through flexible input.
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## Model Details
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- **Model ID**: `FINGU-AI/Qwen2.5-7B-M`
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- **Architecture**: Causal Language Model (LM)
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- **Parameters**: 7 billion
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- **Precision**: Torch BF16 for efficient GPU memory usage
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- **Attention**: SDPA (Scaled Dot-Product Attention)
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- **Primary Use Case**: Translation (e.g., Korean to Uzbek), text generation, and dialogue systems.
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## Example Usage
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### Installation
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Make sure to install the required packages:
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```bash
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pip install torch transformers
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```
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### Loading the Model
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import torch
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# Model and Tokenizer
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model_id = 'FINGU-AI/Qwen2.5-7B-M'
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model = AutoModelForCausalLM.from_pretrained(model_id, attn_implementation="sdpa", torch_dtype=torch.bfloat16)
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model.to('cuda')
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# Input Messages for Translation
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messages = [
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{"role": "system", "content": "translate korean to Uzbek"},
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{"role": "user", "content": """์๋ก์ด ์ํ ๊ณ์ข๋ฅผ ๊ฐ์คํ๋ ์ ์ฐจ๋ ๋ค์๊ณผ ๊ฐ์ต๋๋ค:
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1. ๊ณ์ข ๊ฐ์ค ๋ชฉ์ ๊ณผ ์ ๋ถ ํ์ธ์ ์ํ ์๋ฅ ์ ์ถ
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2. ์๋ฅ ๊ฒํ ๊ณผ์ ์ ๊ฑฐ์น๋ ๊ฒ
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3. ๊ณ ๊ฐ๋์ ์ ์ ํ์ธ ์ ์ฐจ๋ฅผ ์งํํ๋ ๊ฒ
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4. ๋ชจ๋ ์ ์ฐจ๊ฐ ์๋ฃ๋๋ฉด ๊ณ์ข ๊ฐ์ค์ด ๊ฐ๋ฅํฉ๋๋ค.
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๊ณ์ข ๊ฐ์ค์ ์ํ์๋ ๊ฒฝ์ฐ, ์ ๋ถ์ฆ๊ณผ ํจ๊ป ๋ฐฉ๋ฌธํด ์ฃผ์๋ฉด ๋ฉ๋๋ค.
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"""},
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]
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# Tokenize and Generate Response
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input_ids = tokenizer.apply_chat_template(
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messages,
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add_generation_prompt=True,
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return_tensors="pt"
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).to('cuda')
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outputs = model.generate(
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input_ids,
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max_new_tokens=500,
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do_sample=True,
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)
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# Decode and Print the Translation
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response = outputs[0][input_ids.shape[-1]:]
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print(tokenizer.decode(response, skip_special_tokens=True))
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```
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