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@@ -4,6 +4,8 @@ language:
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  - ko
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  library_name: transformers
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  pipeline_tag: text-generation
 
 
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  ---
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  **Model Name**
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  - Open_Ko_SOLAR_DPO_Merge_v0.1
@@ -14,6 +16,10 @@ pipeline_tag: text-generation
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  **Training Corpus**
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  - [maywell/ko_Ultrafeedback_binarized](https://huggingface.co/datasets/maywell/ko_Ultrafeedback_binarized)
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  **Log**
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  - 2024.01.25: Initial version Upload
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@@ -33,4 +39,16 @@ pipeline_tag: text-generation
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  ```
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- **Acknowledgements**
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - ko
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  library_name: transformers
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  pipeline_tag: text-generation
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+ datasets:
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+ - maywell/ko_Ultrafeedback_binarized
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  ---
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  **Model Name**
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  - Open_Ko_SOLAR_DPO_Merge_v0.1
 
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  **Training Corpus**
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  - [maywell/ko_Ultrafeedback_binarized](https://huggingface.co/datasets/maywell/ko_Ultrafeedback_binarized)
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+ **Explanation**
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+ - With base model, apply DPO to the small amount of layers with the dataset written above, saved just an adapter part.
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+ - Merge the base model and the tuned adapter together.
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+
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  **Log**
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  - 2024.01.25: Initial version Upload
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  ```
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+ **Model**
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+ ``` python
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+ from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
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+ model = AutoModelForCausalLM.from_pretrained(
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+ "dddsaty/Open_Ko_SOLAR_DPO_Merge_v0.1",
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+ low_cpu_mem_usage = True,
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+ torch_dtype = torch.float16,
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+ device_map = device_map,
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+ )
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+
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+ tokenizer = AutoTokenizer.from_pretrained("dddsaty/Open_Ko_SOLAR_DPO_Merge_v0.1")
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+
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+ ```