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README.md
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- trl
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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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μλ λνλ₯Ό μμ½ν΄ μ£ΌμΈμ. λν νμμ '#λν μ°Έμ¬μ#: λν λ΄μ©'μ
λλ€.
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### λν >>>{dialogue}
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### μμ½ >>>'''
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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 νμΆ κ³Όμ λ무 μ΄λ €μ... 5μͺ½ μΈκ² μλλ° γ
‘γ
‘ #P02#: λͺ¬λλͺ¬λλκ°λμμ¨ γ
γ
#P01#: 5μͺ½ λμΆ© μμμ νλ¦λλ‘ μ μ¨μΌμ§..μ΄μ 1μͺ½μ ;; 5μͺ½ μλ λ€μ€λ§ μ μ΄μΌμ§ #P02#: μλ... λκ°λΆλμ€μν κ±°κ°μ κ±°μκ½μ±μμμ°μ
#P01#: λͺ»μ¨ μΈλ§μ
μ¨ #P02#: μ΄κ±°μ€κ°λ체μ¬?? #P01#: γ΄γ΄ κ·Έλ₯ κ³Όμ μ κ·Έλμ λ μ§μ¦λ¨'''
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formatted_prompt = prompt_template.format(dialogue=dialogue)
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# ν ν¬λμ΄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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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 ν ν°μ μ¬μ©νμ¬ λͺ
μμ μΌλ‘ μΆλ ₯μ λμ μ§μ .
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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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print(result)
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result = result.split('### μμ½ >>>')[-1].strip()
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print(result)
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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.
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