Update README.md

README.md

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 ---
+language:
+- ko
+
+library_name: transformers
+pipeline_tag: text-generation
 license: cc-by-nc-4.0
 ---
+
+# **Synatra-V0.2-7B**  
+
+Made by StableFluffy
+
+[Visit my website! - Currently on consturction..](https://www.stablefluffy.kr/)
+
+[Join Discord Server](https://discord.gg/HTUBtvjUZa)
+
+## License
+
+This model is strictly [*non-commercial*](https://creativecommons.org/licenses/by-nc/4.0/) (**cc-by-nc-4.0**) use only which takes priority over the **LLAMA 2 COMMUNITY LICENSE AGREEMENT**.
+The "Model" is completely free (ie. base model, derivates, merges/mixes) to use for non-commercial purposes as long as the the included **cc-by-nc-4.0** license in any parent repository, and the non-commercial use statute remains, regardless of other models' licences. 
+The licence can be changed after new model released.
+
+## 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.
+
+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("maywell/Synatra-V0.1-7B")
+tokenizer = AutoTokenizer.from_pretrained("maywell/Synatra-V0.1-7B")
+
+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])
+```
+
+If you run it on oobabooga your prompt would look like this.
+```
+[INST] 링컨에 대해서 알려줘. [/INST]
+```
+
+> Readme format: [beomi/llama-2-ko-7b](https://huggingface.co/beomi/llama-2-ko-7b)
+
+---