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---
datasets:
- TFLai/Turkish-Alpaca
language:
- tr
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
malhajar/phi-2-chat-turkish is a finetuned version of phi-2 using SFT Training.
This model can answer information in turkish language as it is finetuned on a turkish dataset specifically [`Turkish-Alpaca`]( https://huggingface.co/datasets/TFLai/Turkish-Alpaca)
### Model Description
- **Developed by:** [`Mohamad Alhajar`](https://www.linkedin.com/in/muhammet-alhajar/)
- **Language(s) (NLP):** Turkish
- **Finetuned from model:** [`microsoft/phi-2`](https://huggingface.co/microsoft/phi-2)
### Prompt Template
```
### Instruction:
<prompt> (without the <>)
### Response:
```
## 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/phi-2-chat-turkish"
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 = f'''
### Instruction: {question} ### Response:
'''
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,trust_remote_code=True,)
response = tokenizer.decode(output[0])
print(response)
``` |