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--- |
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datasets: |
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- kyujinpy/KOpen-platypus |
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language: |
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- ko |
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- en |
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pipeline_tag: text-generation |
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--- |
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### Model Card for Model ID |
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base_model : [Ko-Llama3-Luxia-8B](https://huggingface.co./saltlux/Ko-Llama3-Luxia-8B) |
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### Basic usage |
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```python |
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# pip install accelerate |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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import torch |
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tokenizer = AutoTokenizer.from_pretrained("MDDDDR/Ko-Luxia-8B-it-v0.1") |
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model = AutoModelForCausalLM.from_pretrained( |
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"MDDDDR/Ko-Luxia-8B-it-v0.1", |
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device_map="auto", |
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torch_dtype=torch.bfloat16 |
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) |
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input_text = "사과가 뭐야?" |
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input_ids = tokenizer(input_text, return_tensors="pt").to("cuda") |
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outputs = model.generate(**input_ids) |
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print(tokenizer.decode(outputs[0])) |
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``` |
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### Training dataset |
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dataset : [kyujinpy/KOpen-platypus](https://huggingface.co./datasets/kyujinpy/KOpen-platypus) |
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### lora_config and bnb_config in Training |
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```python |
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bnd_config = BitsAndBytesConfig( |
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load_in_4bit = True, |
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bnb_4bit_use_double_quant = True, |
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bnb_4bit_quant_type = 'nf4', |
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bnb_4bit_compute_dtype = torch.bfloat16 |
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) |
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lora_config = LoraConfig( |
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r = 16, |
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lora_alpha = 16, |
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lora_dropout = 0.05, |
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target_modules = ['gate_proj', 'up_proj', 'down_proj'] |
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) |
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``` |
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### Hardware |
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RTX 3090 Ti 24GB x 1 |
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### Evaluation Benchmark Results |
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| Tasks |Version|Filter|n-shot| Metric | |Value | |Stderr| |
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|----------------|------:|------|-----:|--------|---|-----:|---|------| |
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|kobest_boolq | 1|none | 0|acc |↑ |0.6425|± |0.0128| |
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| | |none | 0|f1 |↑ |0.6054|± |N/A | |
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|kobest_copa | 1|none | 0|acc |↑ |0.7340|± |0.0140| |
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| | |none | 0|f1 |↑ |0.7333|± |N/A | |
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|kobest_hellaswag| 1|none | 0|acc |↑ |0.4760|± |0.0224| |
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| | |none | 0|acc_norm|↑ |0.6120|± |0.0218| |
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| | |none | 0|f1 |↑ |0.4745|± |N/A | |
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|kobest_sentineg | 1|none | 0|acc |↑ |0.5894|± |0.0247| |
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| | |none | 0|f1 |↑ |0.5682|± |N/A | |
