curl --request POST \ --url https://api.zerogpu.ai/v1/moderations \ --header 'Content-Type: application/json' \ --header 'x-api-key: <api-key>' \ --data '{ "input": [ { "text": "I am so angry at this person that I want to hurt them. They are worthless and should be scared of what I might do next.", "type": "text" } ], "model": "zlm-v1-moderation-edge"}'
import requests
url = "https://api.zerogpu.ai/v1/moderations"
payload = {
"input": [
{
"text": "I am so angry at this person that I want to hurt them. They are worthless and should be scared of what I might do next.",
"type": "text"
}
],
"model": "zlm-v1-moderation-edge"
}
headers = {
"x-api-key": "<api-key>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)
const options = {
method: 'POST',
headers: {'x-api-key': '<api-key>', 'Content-Type': 'application/json'},
body: JSON.stringify({
input: [
{
text: 'I am so angry at this person that I want to hurt them. They are worthless and should be scared of what I might do next.',
type: 'text'
}
],
model: 'zlm-v1-moderation-edge'
})
};
fetch('https://api.zerogpu.ai/v1/moderations', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));
false
package main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://api.zerogpu.ai/v1/moderations"
payload := strings.NewReader("{\n \"input\": [\n {\n \"text\": \"I am so angry at this person that I want to hurt them. They are worthless and should be scared of what I might do next.\",\n \"type\": \"text\"\n }\n ],\n \"model\": \"zlm-v1-moderation-edge\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("x-api-key", "<api-key>")
req.Header.Add("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}
require 'uri'
require 'net/http'
url = URI("https://api.zerogpu.ai/v1/moderations")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["x-api-key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"input\": [\n {\n \"text\": \"I am so angry at this person that I want to hurt them. They are worthless and should be scared of what I might do next.\",\n \"type\": \"text\"\n }\n ],\n \"model\": \"zlm-v1-moderation-edge\"\n}"
response = http.request(request)
puts response.read_body
Model details for zlm-v1-moderation-edge. OpenAI-compatible moderation, benchmarked against omni-moderation-latest.
POST
/
moderations
zlm-v1-moderation-edge: Moderations
curl --request POST \ --url https://api.zerogpu.ai/v1/moderations \ --header 'Content-Type: application/json' \ --header 'x-api-key: <api-key>' \ --data '{ "input": [ { "text": "I am so angry at this person that I want to hurt them. They are worthless and should be scared of what I might do next.", "type": "text" } ], "model": "zlm-v1-moderation-edge"}'
import requests
url = "https://api.zerogpu.ai/v1/moderations"
payload = {
"input": [
{
"text": "I am so angry at this person that I want to hurt them. They are worthless and should be scared of what I might do next.",
"type": "text"
}
],
"model": "zlm-v1-moderation-edge"
}
headers = {
"x-api-key": "<api-key>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)
const options = {
method: 'POST',
headers: {'x-api-key': '<api-key>', 'Content-Type': 'application/json'},
body: JSON.stringify({
input: [
{
text: 'I am so angry at this person that I want to hurt them. They are worthless and should be scared of what I might do next.',
type: 'text'
}
],
model: 'zlm-v1-moderation-edge'
})
};
fetch('https://api.zerogpu.ai/v1/moderations', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));
false
package main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://api.zerogpu.ai/v1/moderations"
payload := strings.NewReader("{\n \"input\": [\n {\n \"text\": \"I am so angry at this person that I want to hurt them. They are worthless and should be scared of what I might do next.\",\n \"type\": \"text\"\n }\n ],\n \"model\": \"zlm-v1-moderation-edge\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("x-api-key", "<api-key>")
req.Header.Add("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}
require 'uri'
require 'net/http'
url = URI("https://api.zerogpu.ai/v1/moderations")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["x-api-key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"input\": [\n {\n \"text\": \"I am so angry at this person that I want to hurt them. They are worthless and should be scared of what I might do next.\",\n \"type\": \"text\"\n }\n ],\n \"model\": \"zlm-v1-moderation-edge\"\n}"
response = http.request(request)
puts response.read_body
This model is routable on /v1/moderations and on /v1/systemone (see
System One). Send the text to classify as
input — a string, an array of strings, or an array of
{"type": "text", "text": "…"} content parts. The response is OpenAI’s native
moderations envelope, { id, model, results[] }, with each result carrying a
flagged verdict, per-category categories booleans, and calibrated
category_scores — so it drops into any pipeline written against
omni-moderation-latest.
ZeroGPU’s moderation model screens text for unsafe, harmful, or policy-sensitive content and returns the complete OpenAI 13-category taxonomy (a flagged verdict, per-category booleans, and calibrated category_scores), so it drops into any pipeline written against omni-moderation-latest. Under the hood it’s an 86M-parameter DeBERTa encoder with a shared trunk feeding one binary safe/unsafe head and 13 category heads, with per-category thresholds calibrated on held-out validation data. In head-to-head benchmarks against OpenAI omni-moderation it wins the binary safe/unsafe decision (0.899 vs 0.853 F1) and 9 of 13 harm categories, with the largest gains on graphic violence, illicit content, and self-harm, while returning verdicts 1.2–1.8× faster at the median on production-range inputs, because inference is co-located at the edge instead of a round trip to a central API. Moderation sits inline in front of every response your app serves; this is the model that’s fast and accurate enough to live there.
It also answers System One decisions on /v1/systemone: ask whether content is unsafe or brand safe (noul), which moderation category applies (choice), or how severe a violation is (score).References:Moderation benchmark • Terms • Privacy
Text to classify. Accepts a single string, an array of strings (one result per element), or an array of content parts ({ "type": "text", "text": "..." }) that form a single multi-modal input.
Required string length: 1 - 131072
Response
Success
OpenAI-compatible moderations envelope. One results entry per input.
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