---
library_name: transformers
tags:
- trl
- sft
---

## Download the model

```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

model_path = "Mike0307/Phi-3-mini-4k-instruct-chinese-lora"
base_model = AutoModelForCausalLM.from_pretrained(
    model_path, 
    device_map="mps", # FIX mps if not MacOS
    torch_dtype=torch.float32, 
    trust_remote_code=True,
)
tokenizer = AutoTokenizer.from_pretrained(model_path)
```

## Example of inference

```python
input_text = "<|user|>將這五種動物分成兩組。\n老虎、鯊魚、大象、鯨魚、袋鼠 <|end|>\n<|assistant|>"
inputs = tokenizer(input_text, return_tensors="pt").to(torch.device("mps")) # FIX mps if not MacOS

outputs = base_model.generate(
    **inputs, 
    temperature = 0.0,
    max_length = 500,
    do_sample = False
)

generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True, predict_with_generate=True)
print(generated_text)
```