README.md

---
datasets:
- atasoglu/databricks-dolly-15k-tr
language:
- tr
---

# Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. -->
malhajar/Llama-2-13b-chat-dolly-tr is a finetuned version of Llama-2-13b-hf using SFT Training.
This model can answer information in turkish language as it is finetuned on a turkish dataset specifically [`databricks-dolly-15k-tr`]( https://huggingface.co/datasets/atasoglu/databricks-dolly-15k-tr) 

![llama](./llama.png)

### Model Description

- **Developed by:** [`Mohamad Alhajar`](https://www.linkedin.com/in/muhammet-alhajar/) 
- **Language(s) (NLP):** Turkish
- **Finetuned from model:** [`meta-llama/Llama-2-13b-hf`](https://huggingface.co/meta-llama/Llama-2-13b-hf)

### Prompt Template

```
<s>[INST] <prompt> [/INST] 
```

## How to Get Started with the Model

Use the code sample provided in the original post to interact with the model.
```python
from transformers import AutoTokenizer,AutoModelForCausalLM
 
model_id = "malhajar/Llama-2-7b-chat-dolly-tr"
model = AutoModelForCausalLM.from_pretrained(model_name_or_path,
                                             device_map="auto",
                                             torch_dtype=torch.float16,
                                             revision="main")

tokenizer = AutoTokenizer.from_pretrained(model_id)

question: "Türkiyenin en büyük şehir nedir?"
# For generating a response
prompt = '''
<s>[INST] {question}  [/INST]
'''
input_ids = tokenizer(prompt, return_tensors="pt").input_ids
output = model.generate(inputs=input_ids,max_new_tokens=512,pad_token_id=tokenizer.eos_token_id,top_k=50, do_sample=True,repetition_penalty=1.3
        top_p=0.95)
response = tokenizer.decode(output[0])

print(response)
```