Zyphra Thought
ZUNA1.1
Efficient open foundation model for EEG reconstruction, denoising, and upsampling.
About
ZUNA1.1 is Zyphra's open, Apache 2.0-licensed EEG foundation model that reconstructs, denoises, and upsamples EEG recordings across arbitrary channel layouts and time segments. This 380M-parameter diffusion autoencoder conditions on the true 3D positions of each electrode, works on essentially any montage from 4-channel consumer headbands to 256-channel research caps without retraining and delivers high-fidelity reconstruction across variable-length real-world recordings. ZUNA1.1 can accept both a 0.5 s trial snippet and a 30 s continuous stretch, with no retraining or reconfiguration.
Performance
ZUNA1.1 was trained on roughly 3.5 million channel-hours of public EEG using quality-aware preprocessing that scores every channel-second, letting it learn from partially-noisy recordings that conventional pipelines discard. Combined with training on four realistic channel-dropout patterns drawn from how EEG fails in practice, this produces consistently high-fidelity reconstruction across montages, sequence lengths, and noise conditions, outperforming classical interpolation methods.
API usage
import os
from openai import OpenAI
client = OpenAI(
api_key=os.getenv("ZYPHRA_API_KEY"),
base_url="https://api.zyphracloud.com/api/v1",
)
response = client.chat.completions.create(
model="zyphra/ZUNA1.1",
messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.ZYPHRA_API_KEY,
baseURL: "https://api.zyphracloud.com/api/v1",
});
const response = await client.chat.completions.create({
model: "zyphra/ZUNA1.1",
messages: [{ role: "user", content: "Hello!" }],
});
console.log(response.choices[0].message.content);curl https://api.zyphracloud.com/api/v1/chat/completions \
-H "Authorization: Bearer $ZYPHRA_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "zyphra/ZUNA1.1",
"messages": [{"role": "user", "content": "Hello!"}]
}'