---
base_model: malhajar/phi-2-chat
datasets:
- yahma/alpaca-cleaned
inference: false
language:
- en
model_creator: malhajar
model_name: phi-2-chat
pipeline_tag: text-generation
quantized_by: afrideva
tags:
- gguf
- ggml
- quantized
- q2_k
- q3_k_m
- q4_k_m
- q5_k_m
- q6_k
- q8_0
---
# malhajar/phi-2-chat-GGUF

Quantized GGUF model files for [phi-2-chat](https://huggingface.co/malhajar/phi-2-chat) from [malhajar](https://huggingface.co/malhajar)


| Name | Quant method | Size |
| ---- | ---- | ---- |
| [phi-2-chat.fp16.gguf](https://huggingface.co/afrideva/phi-2-chat-GGUF/resolve/main/phi-2-chat.fp16.gguf) | fp16 | 5.56 GB  |
| [phi-2-chat.q2_k.gguf](https://huggingface.co/afrideva/phi-2-chat-GGUF/resolve/main/phi-2-chat.q2_k.gguf) | q2_k | 1.17 GB  |
| [phi-2-chat.q3_k_m.gguf](https://huggingface.co/afrideva/phi-2-chat-GGUF/resolve/main/phi-2-chat.q3_k_m.gguf) | q3_k_m | 1.48 GB  |
| [phi-2-chat.q4_k_m.gguf](https://huggingface.co/afrideva/phi-2-chat-GGUF/resolve/main/phi-2-chat.q4_k_m.gguf) | q4_k_m | 1.79 GB  |
| [phi-2-chat.q5_k_m.gguf](https://huggingface.co/afrideva/phi-2-chat-GGUF/resolve/main/phi-2-chat.q5_k_m.gguf) | q5_k_m | 2.07 GB  |
| [phi-2-chat.q6_k.gguf](https://huggingface.co/afrideva/phi-2-chat-GGUF/resolve/main/phi-2-chat.q6_k.gguf) | q6_k | 2.29 GB  |
| [phi-2-chat.q8_0.gguf](https://huggingface.co/afrideva/phi-2-chat-GGUF/resolve/main/phi-2-chat.q8_0.gguf) | q8_0 | 2.96 GB  |



## Original Model Card:
# Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. -->
malhajar/phi-2-chat is a finetuned version of [`phi-2`]( https://huggingface.co/microsoft/phi-2) using SFT Training.
This model can answer information in a chat format as it is finetuned specifically on instructions specifically [`alpaca-cleaned`]( https://huggingface.co/datasets/yahma/alpaca-cleaned) 

### 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"
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 = '''
### 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)
```