Create README.md

README.md

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+---
+tags:
+    - text-generation
+license: cc-by-nc-4.0
+language:
+    - ko
+base_model: Edentns/DataVortexS-10.7B-dpo-v1.11
+pipeline_tag: text-generation
+---
+
+
+## **Model Details**
+
+### **Base Model**
+
+[Edentns/DataVortexS-10.7B-dpo-v1.11](https://huggingface.co/Edentns/DataVortexS-10.7B-dpo-v1.11)
+
+
+### **Trained On**
+
+-   **GPU**: A100 80GB 8ea
+
+### **Instruction format**
+
+It follows **Alpaca (Chat)** format.
+
+
+
+## **Implementation Code**
+
+This model contains the chat_template instruction format.  
+You can use the code below.
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+device = "cuda" # the device to load the model onto
+
+model = AutoModelForCausalLM.from_pretrained("Raphael21/Raphael21-SOLAR-10.7B")
+tokenizer = AutoTokenizer.from_pretrained("Raphael21/Raphael21-SOLAR-10.7B")
+
+messages = [
+    {"role": "system", "content": "당신은 사람들이 정보를 찾을 수 있도록 도와주는 인공지능 비서입니다."},
+    {"role": "user", "content": "이순신 장군에 대해 설명해줘"},
+]
+
+encodeds = tokenizer.apply_chat_template(messages, return_tensors="pt")
+
+model_inputs = encodeds.to(device)
+model.to(device)
+
+generated_ids = model.generate(model_inputs, max_new_tokens=1000, do_sample=True)
+decoded = tokenizer.batch_decode(generated_ids)
+print(decoded[0])
+```
+
+## **License**
+
+This model is licensed under the [cc-by-nc-4.0](https://creativecommons.org/licenses/by-nc/4.0/). which allows others to share and adapt the model for non-commercial purposes.
+
+