Update README.md

README.md

@@ -1,3 +1,63 @@
 ---
+language:
+- ko
+
+library_name: transformers
+pipeline_tag: text-generation
 license: cc-by-nc-4.0
 ---
+
+# **Synatra-V0.1-7B**  
+
+## Model Details
+
+**Base Model**  
+[mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1)    
+
+**Trained On**  
+A6000 48GB * 8
+
+## Instruction format
+
+In order to leverage instruction fine-tuning, your prompt should be surrounded by `[INST]` and `[/INST]` tokens. The very first instruction should begin with a begin of sentence id. The next instructions should not. The assistant generation will be ended by the end-of-sentence token id.
+Plus, It is strongly recommended to add a space at the end of the prompt.
+
+E.g.
+```
+text = "<s>[INST] 아이작 뉴턴의 업적을 알려줘. [/INST] "
+```
+
+# **Model Benchmark**
+
+Preparing...
+  
+# Implementation Code
+
+Since, chat_template already contains insturction format above.
+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("mistralai/Mistral-7B-Instruct-v0.1")
+tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1")
+
+messages = [
+    {"role": "user", "content": "What is your favourite condiment?"},
+]
+
+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])
+```
+
+> Readme format: [beomi/llama-2-ko-7b](https://huggingface.co/beomi/llama-2-ko-7b)
+
+---