Upload README.md

README.md

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 ---
+language:
+- ko
+datasets: 
+- kyujinpy/Ko-various-dataset
+library_name: transformers
+pipeline_tag: text-generation
 license: cc-by-nc-sa-4.0
 ---
+
+# **⭐My custom LLM 13B⭐**  
+
+## Model Details   
+**Model Developers**  
+- Kyujin Han (kyujinpy)  
+
+**Model Architecture**  
+- My custom LLM 13B is an auto-regressive language model based on the LLaMA2 transformer architecture.  
+
+**Base Model**   
+- [beomi/llama-2-koen-13b](https://huggingface.co/beomi/llama-2-koen-13b)   
+
+**Training Dataset**   
+- [kyujinpy/Ko-various-dataset](https://huggingface.co/datasets/kyujinpy/Ko-various-dataset). 
+
+---  
+# Model comparisons
+> Ko-LLM leaderboard(11/27; [link](https://huggingface.co/spaces/upstage/open-ko-llm-leaderboard))
+   
+| Model | Average | Ko-ARC | Ko-HellaSwag | Ko-MMLU | Ko-TruthfulQA | Ko-CommonGen V2 |
+| --- | --- | --- | --- | --- | --- | --- |
+| ⭐My custom LLM 13B-v1⭐ | 50.19 | 45.99 | 56.93 | 41.78 | 41.66 | **64.58** | 
+| ⭐My custom LLM 13B v2⭐ | NaN | NaN | NaN | NaN | NaN | NaN | 
+| ⭐My custom LLM 13B v3⭐ | NaN | NaN | NaN | NaN | NaN | NaN | 
+
+
+# Implementation Code
+```python
+### KO-Platypus
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+repo = "PracticeLLM/Custom-KoLLM-13B-v3"
+OpenOrca = AutoModelForCausalLM.from_pretrained(
+        repo,
+        return_dict=True,
+        torch_dtype=torch.float16,
+        device_map='auto'
+)
+OpenOrca_tokenizer = AutoTokenizer.from_pretrained(repo)
+```
+
+---