Back to Transformers

Apertus

docs/source/en/model_doc/apertus.md

5.8.02.7 KB
Original Source
<!--Copyright 2025 The HuggingFace Team and the Swiss AI Initiative. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be rendered properly in your Markdown viewer. -->

This model was released on 2025-09-02 and added to Hugging Face Transformers on 2025-08-28.

Apertus

<div style="float: right;"> <div class="flex flex-wrap space-x-1">
</div>
</div>

Overview

Apertus 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