GPAI Ledger › Apertus (Swiss AI Initiative) › Capture 11 Aug 2026

Apertus — capture 20260811T102206Z

Provider	Swiss AI Initiative
Target	provider site — https://huggingface.co/swiss-ai/Apertus-70B-2509/blob/main/Apertus_EU_Public_Summary.pdf
Fetched (UTC)	2026-08-11T10:22:06Z
Stored file	6ad4b1e7a61c9cfcb2482c8392d5ec65952a61113392b9e00b389af495eef86e.html.txt (138,616 bytes) (served with a .txt suffix so the captured page cannot run scripts on this site; bytes are identical — the SHA-256 verifies against this file)
SHA-256	`6ad4b1e7a61c9cfcb2482c8392d5ec65952a61113392b9e00b389af495eef86e`
OpenTimestamps proof	6ad4b1e7a61c9cfcb2482c8392d5ec65952a61113392b9e00b389af495eef86e.html.ots (calendar-attested; anchored in bitcoin over time)
Wayback	Wayback snapshot, 2026-06-21 22:10 UTC (pre-existing snapshot returned by the Wayback Machine — witnesses the page before this capture)
Prior capture of this target	`— first capture of this target`
Notes	text_sha256 recorded 20 Aug 2026 from the extracted.txt stored at capture time (bootstrap captures predate this field); raw bytes unchanged

Verify: sha256sum 6ad4b1e7a61c9cfcb2482c8392d5ec65952a61113392b9e00b389af495eef86e.html.txt must equal the hash above (the filename IS the expected hash); ots verify 6ad4b1e7a61c9cfcb2482c8392d5ec65952a61113392b9e00b389af495eef86e.html.ots -f 6ad4b1e7a61c9cfcb2482c8392d5ec65952a61113392b9e00b389af495eef86e.html.txt (opentimestamps.org) proves the capture time (fresh proofs report 'pending' until bitcoin-anchored, typically within a day).

Extracted text

Machine-extracted text (layout may be lost; the authoritative content is the stored file above).

Apertus_EU_Public_Summary.pdf · swiss-ai/Apertus-70B-2509 at main

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swiss-ai

/

Apertus-70B-2509

like

158

Follow

Swiss AI Initiative

1.34k

Text Generation

Transformers

Safetensors

apertus

multilingual

compliant

swiss-ai

arxiv:

2509.14233

License:

apache-2.0

Model card

Files

Files and versions

xet

 Deploy

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 Use this model

Instructions to use swiss-ai/Apertus-70B-2509 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

Transformers

How to use swiss-ai/Apertus-70B-2509 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="swiss-ai/Apertus-70B-2509")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("swiss-ai/Apertus-70B-2509")
model = AutoModelForCausalLM.from_pretrained("swiss-ai/Apertus-70B-2509", device_map="auto")

Notebooks

Google Colab

Kaggle

Local Apps

Settings

vLLM

How to use swiss-ai/Apertus-70B-2509 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "swiss-ai/Apertus-70B-2509"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "swiss-ai/Apertus-70B-2509",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'
Use Docker

docker model run hf.co/swiss-ai/Apertus-70B-2509

SGLang

How to use swiss-ai/Apertus-70B-2509 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "swiss-ai/Apertus-70B-2509" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "swiss-ai/Apertus-70B-2509",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'
Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "swiss-ai/Apertus-70B-2509" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "swiss-ai/Apertus-70B-2509",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner

How to use swiss-ai/Apertus-70B-2509 with Docker Model Runner:

docker model run hf.co/swiss-ai/Apertus-70B-2509

 main

Apertus-70B-2509

/

Apertus_EU_Public_Summary.pdf

mjaggi

initial EU AI act documentation

2614136

verified

11 months ago

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 329 kB

Xet Pointer Details

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Xet hash:

95f599d066dce5869d06e9890dd28ce2011560e35531e177913bfa55e9f452b5

Size of remote file:

329 kB

·

SHA256:

787b7e5122765cd8f5a5832a248bd21843c2e300d9e36b5832246f9bd0dd6010

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