inference-net/schematron-v2-small
Schematron V2 Small is a 3B-parameter HTML-to-JSON extraction model from Inference.net. It prioritizes extraction quality for complex schemas and long pages. Extraction instructions must be supplied through a JSON schema...
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Charged from your UAI balance
Same API key and billing flow
This page exists for direct linking, onboarding, and SEO. The same model row powers /v1/models, the public catalog, the app pricing screen, and request validation for /v1/chat/completions.
The same model route, but with one account, one balance, and one API shape.
Inference.net: Schematron V2 Small exposes 128K tokens, which makes it a good fit for large documents, transcripts, and retrieval-heavy chat flows.
Inference.net: Schematron V2 Small is positioned well for chat UIs, demos, and agent loops where faster turn time matters.
Call inference-net/schematron-v2-small with the same UAI API key, the same /v1/chat/completions shape, and the same request validation used across the rest of the catalog.
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Use this model with your UAI key over the standard OpenAI-compatible route.
Create a key in API Keys, then send requests to https://uai.sh/v1/chat/completions.
curl https://uai.sh/v1/chat/completions \
-H "Authorization: Bearer uai-YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "inference-net/schematron-v2-small",
"messages": [{"role": "user", "content": "Say hi in one short sentence."}],
"stream": false
}'
from openai import OpenAI
client = OpenAI(base_url="https://uai.sh/v1", api_key="uai-YOUR_API_KEY")
response = client.chat.completions.create(
model="inference-net/schematron-v2-small",
messages=[{"role": "user", "content": "Say hi in one short sentence."}],
stream=False
)
print(response.choices[0].message.content)
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://uai.sh/v1",
apiKey: "uai-YOUR_API_KEY"
});
const response = await client.chat.completions.create({
model: "inference-net/schematron-v2-small",
messages: [{ role: "user", content: "Say hi in one short sentence." }],
stream: false
});
console.log(response.choices[0].message.content);
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