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*This model was released on 2025-06-30 and added to Hugging Face Transformers on 2025-07-21.*

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    <div class="flex flex-wrap space-x-1">
        <img alt="PyTorch" src="https://img.shields.io/badge/PyTorch-DE3412?style=flat&logo=pytorch&logoColor=white">
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# Ernie 4.5

## Overview

The Ernie 4.5 model was released in the [Ernie 4.5 Model Family](https://ernie.baidu.com/blog/posts/ernie4.5/) release by baidu.
This family of models contains multiple different architectures and model sizes. This model in specific targets the base text
model without mixture of experts (moe) with 0.3B parameters in total. It uses the standard [Llama](./llama) at its core.

Other models from the family can be found at [Ernie 4.5 Moe](./ernie4_5_moe).

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    <img src="https://ernie.baidu.com/blog/posts/ernie4.5/overview.png"/>
</div>

## Usage Tips

### Generate text

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

model_name = "baidu/ERNIE-4.5-0.3B-PT"

# load the tokenizer and the model
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
    model_name,
    device_map="auto",
    dtype=torch.bfloat16,
)

# prepare the model input
inputs = tokenizer("Hey, are you conscious? Can you talk to me?", return_tensors="pt")
prompt = "Hey, are you conscious? Can you talk to me?"
messages = [
    {"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True
)
model_inputs = tokenizer([text], add_special_tokens=False, return_tensors="pt").to(model.device)

# conduct text completion
generated_ids = model.generate(
    **model_inputs,
    max_new_tokens=32,
)
output_ids = generated_ids[0][len(model_inputs.input_ids[0]):].tolist()

# decode the generated ids
generate_text = tokenizer.decode(output_ids, skip_special_tokens=True)
```

This model was contributed by [Anton Vlasjuk](https://huggingface.co/AntonV).
The original code can be found [here](https://github.com/PaddlePaddle/ERNIE).

## Ernie4_5Config

[[autodoc]] Ernie4_5Config

## Ernie4_5Model

[[autodoc]] Ernie4_5Model
    - forward

## Ernie4_5ForCausalLM

[[autodoc]] Ernie4_5ForCausalLM
    - forward
