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  - trl
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  ---
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- # korean dialogue summary fine-tuned model
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  - **Developed by:** lwef
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  - **License:** apache-2.0
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  - **Finetuned from model :** beomi/Llama-3-Open-Ko-8B
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  This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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- [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
 
 
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  - trl
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  ---
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  - **Developed by:** lwef
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  - **License:** apache-2.0
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  - **Finetuned from model :** beomi/Llama-3-Open-Ko-8B
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+ # korean dialogue summary fine-tuned model
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+ # how to use
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+ ```python
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+ prompt_template = '''
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+ μ•„λž˜ λŒ€ν™”λ₯Ό μš”μ•½ν•΄ μ£Όμ„Έμš”. λŒ€ν™” ν˜•μ‹μ€ '#λŒ€ν™” μ°Έμ—¬μž#: λŒ€ν™” λ‚΄μš©'μž…λ‹ˆλ‹€.
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+ ### λŒ€ν™” >>>{dialogue}
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+
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+ ### μš”μ•½ >>>'''
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+
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+ if True:
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+ from unsloth import FastLanguageModel
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+ model, tokenizer = FastLanguageModel.from_pretrained(
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+ model_name = "lwef/llm-bench-upload-1", # YOUR MODEL YOU USED FOR TRAINING
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+ max_seq_length = 2048,
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+ dtype = None,
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+ load_in_4bit = True,
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+ )
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+ FastLanguageModel.for_inference(model) # Enable native 2x faster inference
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+ dialogue = '''#P01#: μ•„ ν–‰μ‚Ά 과제 λ„ˆλ¬΄ μ–΄λ €μ›Œ... 5μͺ½ μ“Έκ²Œ μ—†λŠ”λ° γ…‘γ…‘ #P02#: λͺ¬λƒλͺ¬λƒλ„ˆκ°€λ”μž˜μ¨ γ…Žγ…Ž #P01#: 5μͺ½ λŒ€μΆ© μ˜μ‹μ˜ νλ¦„λŒ€λ‘œ μ­‰ 써야지..이제 1μͺ½μ”€ ;; 5μͺ½ μ—λŠ” λ„€μ€„λ§Œ 적어야지 #P02#: μ•ˆλŒ€... λ­”κ°€λΆ„λŸ‰μ€‘μš”ν• κ±°κ°™μ•„ κ±°μ˜κ½‰μ±„μ›Œμ„œμ“°μ…ˆ #P01#: λͺ»μ¨ 쓸말업써 #P02#: μ΄κ±°μ€‘κ°„λŒ€μ²΄μ—¬?? #P01#: γ„΄γ„΄ κ·Έλƒ₯ κ³Όμ œμž„ κ·Έλž˜μ„œ 더 μ§œμ¦λ‚¨'''
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+
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+ formatted_prompt = prompt_template.format(dialogue=dialogue)
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+
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+ # ν† ν¬λ‚˜μ΄μ§•
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+ inputs = tokenizer(
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+ formatted_prompt,
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+ return_tensors="pt"
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+ ).to("cuda")
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+
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+ outputs = model.generate(
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+ **inputs,
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+ max_new_tokens = 128,
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+ eos_token_id=tokenizer.eos_token_id, # EOS 토큰을 μ‚¬μš©ν•˜μ—¬ λͺ…μ‹œμ μœΌλ‘œ 좜λ ₯의 끝을 지정.
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+ use_cache = True
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+ )
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+ decoded_outputs = tokenizer.batch_decode(outputs, skip_special_tokens=True)
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+ result = decoded_outputs[0]
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+
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+ print(result)
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+ result = result.split('### μš”μ•½ >>>')[-1].strip()
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+ print(result)
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+ ```
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+
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  This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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+ [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
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+ I highly recommend checking the Unsloth notebook.