Update README.md

README.md

@@ -7,3 +7,53 @@ library_name: transformers
 pipeline_tag: text-generation
 license: mit
 ---
+# **etri-ones-solar**  
+
+## Model Details   
+**Model Developers**  
+- the model is fine-tuned by open instruction dataset
+
+**Model Architecture**  
+- this model is an auto-regressive language model based on the solar transformer architecture.  
+
+**Base Model**   
+- solar https://huggingface.co/upstage/SOLAR-10.7B-v1.0  
+
+**Training Dataset**   
+- 
+
+---  
+# Model comparisons1
+> comming soon
+   
+| Model | Average | Ko-ARC | Ko-HellaSwag | Ko-MMLU | Ko-TruthfulQA | Ko-CommonGen V2 |
+| --- | --- | --- | --- | --- | --- | --- |
+| **[...your_model_name...]** | NaN | NaN | NaN | NaN | NaN | NaN | 
+  
+---  
+# Model comparisons2
+> AI-Harness evaluation; [link](https://github.com/Beomi/ko-lm-evaluation-harness)   
+   
+| Model | Copa | Copa | HellaSwag | HellaSwag | BoolQ | BoolQ | Sentineg | Sentineg |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- |
+|  | 0-shot | 5-shot | 0-shot | 5-shot | 0-shot | 5-shot | 0-shot | 5-shot |
+| **[...your_model_name...]** | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
+  
+---
+# Implementation Code
+```python
+### KO-Platypus
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+repo = "[...your_model_repo...]"
+OpenOrca = AutoModelForCausalLM.from_pretrained(
+        repo,
+        return_dict=True,
+        torch_dtype=torch.float16,
+        device_map='auto'
+)
+OpenOrca_tokenizer = AutoTokenizer.from_pretrained(repo)
+```
+
+---