File size: 1,753 Bytes
d10f73b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 |
---
datasets:
- yahma/alpaca-cleaned
language:
- en
---
# 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)
``` |