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transformers/docs/source/en/model_doc/ernie4_5.md
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<!--Copyright 2025 The HuggingFace Team. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
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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 style="float: right;">
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<div class="flex flex-wrap space-x-1">
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<img alt="PyTorch" src="https://img.shields.io/badge/PyTorch-DE3412?style=flat&logo=pytorch&logoColor=white">
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<img alt="FlashAttention" src="https://img.shields.io/badge/%E2%9A%A1%EF%B8%8E%20FlashAttention-eae0c8?style=flat">
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<img alt="SDPA" src="https://img.shields.io/badge/SDPA-DE3412?style=flat&logo=pytorch&logoColor=white">
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<img alt="Tensor parallelism" src="https://img.shields.io/badge/Tensor%20parallelism-06b6d4?style=flat&logoColor=white">
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</div>
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</div>
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# Ernie 4.5
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## Overview
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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.
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This family of models contains multiple different architectures and model sizes. This model in specific targets the base text
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model without mixture of experts (moe) with 0.3B parameters in total. It uses the standard [Llama](./llama) at its core.
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Other models from the family can be found at [Ernie 4.5 Moe](./ernie4_5_moe).
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<div class="flex justify-center">
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<img src="https://ernie.baidu.com/blog/posts/ernie4.5/overview.png"/>
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</div>
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## Usage Tips
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### Generate text
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```python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = "baidu/ERNIE-4.5-0.3B-PT"
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# load the tokenizer and the model
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(
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model_name,
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device_map="auto",
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dtype=torch.bfloat16,
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)
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# prepare the model input
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inputs = tokenizer("Hey, are you conscious? Can you talk to me?", return_tensors="pt")
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prompt = "Hey, are you conscious? Can you talk to me?"
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messages = [
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{"role": "user", "content": prompt}
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]
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True
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)
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model_inputs = tokenizer([text], add_special_tokens=False, return_tensors="pt").to(model.device)
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# conduct text completion
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generated_ids = model.generate(
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**model_inputs,
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max_new_tokens=32,
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)
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output_ids = generated_ids[0][len(model_inputs.input_ids[0]):].tolist()
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# decode the generated ids
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generate_text = tokenizer.decode(output_ids, skip_special_tokens=True)
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```
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This model was contributed by [Anton Vlasjuk](https://huggingface.co/AntonV).
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The original code can be found [here](https://github.com/PaddlePaddle/ERNIE).
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## Ernie4_5Config
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[[autodoc]] Ernie4_5Config
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## Ernie4_5Model
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[[autodoc]] Ernie4_5Model
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- forward
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## Ernie4_5ForCausalLM
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[[autodoc]] Ernie4_5ForCausalLM
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- forward
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