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+*This model was contributed to Hugging Face Transformers on 2025-07-21.*
+
+<div style="float: right;">
+    <div class="flex flex-wrap space-x-1">
+        <img alt="FlashAttention" src="https://img.shields.io/badge/%E2%9A%A1%EF%B8%8E%20FlashAttention-eae0c8?style=flat">
+        <img alt="SDPA" src="https://img.shields.io/badge/SDPA-DE3412?style=flat&logo=pytorch&logoColor=white">
+        <img alt="Tensor parallelism" src="https://img.shields.io/badge/Tensor%20parallelism-06b6d4?style=flat&logoColor=white">
+    </div>
+</div>
+
+# 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) and [Ernie 4.5 VL MoE](./ernie4_5_vl_moe.md).
+
+<div class="flex justify-center">
+    <img src="https://ernie.baidu.com/blog/posts/ernie4.5/overview.png"/>
+</div>
+
+## Usage Tips
+
+### Generate text
+
+```python
+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",
+)
+
+# prepare the model input
+inputs = tokenizer("Hey, are you conscious? Can you talk to me?", return_tensors="pt").to(model.device)
+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