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+<!--Copyright 2025 The HuggingFace Team and the Swiss AI Initiative. All rights reserved.
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+*This model was contributed to Hugging Face Transformers on 2025-08-28.*
+
+# Apertus
+
+<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>
+
+## Overview
+
+[Apertus](https://www.swiss-ai.org) is a family of large language models from the Swiss AI Initiative.
+
+> [!TIP]
+> Coming soon
+
+The example below demonstrates how to generate text with [`Pipeline`] or the [`AutoModel`], and from the command line.
+
+<hfoptions id="usage">
+<hfoption id="Pipeline">
+
+```python
+from transformers import pipeline
+
+
+pipeline = pipeline(
+    task="text-generation",
+    model="swiss-ai/Apertus-8B",
+    device=0
+)
+pipeline("Plants create energy through a process known as")
+```
+
+</hfoption>
+<hfoption id="AutoModel">
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+
+tokenizer = AutoTokenizer.from_pretrained(
+    "swiss-ai/Apertus-8B",
+)
+model = AutoModelForCausalLM.from_pretrained(
+    "swiss-ai/Apertus-8B",
+    device_map="auto",
+    attn_implementation="sdpa"
+)
+input_ids = tokenizer("Plants create energy through a process known as", return_tensors="pt").to(model.device)
+
+output = model.generate(**input_ids)
+print(tokenizer.decode(output[0], skip_special_tokens=True))
+```
+
+</hfoption>
+</hfoptions>
+
+## ApertusConfig
+
+[[autodoc]] ApertusConfig
+
+## ApertusModel
+
+[[autodoc]] ApertusModel
+    - forward
+
+## ApertusForCausalLM
+
+[[autodoc]] ApertusForCausalLM
+    - forward
+
+## ApertusForTokenClassification
+
+[[autodoc]] ApertusForTokenClassification
+    - forward