A pretrained warhammer unit type classifier that sorts an image into one of 10 categories — what type of Warhammer unit it is. Use the warhammer unit type API immediately, no training required, then adapt it to your own data when you need more.
Drop in a photo and get the prediction back. No signup, no setup.
A sample of the 26 labels this pretrained classifier chooses between.
Need a label that isn't here? Clone the classifier into your Nyckel console and edit the label set to fit your data.
Once you've added this classifier to your console, you get your own copy of it behind your own endpoint. Invoke it with any HTTP client:
curl
curl -X POST "https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke" \
-H "Authorization: Bearer $NYCKEL_ACCESS_TOKEN" \
-H "Content-Type: application/json" \
-d '{"data": "https://example.com/photo.jpg"}'Python
import requests
# Get an access token: https://www.nyckel.com/docs/api/overview/authentication/
token = "YOUR_ACCESS_TOKEN"
response = requests.post(
"https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke",
headers={"Authorization": "Bearer " + token},
json={"data": "https://example.com/photo.jpg"},
)
print(response.json())Example response
{
"labelName": "Artillery",
"labelId": "label_...",
"confidence": 0.92
}Trained on a Nyckel-curated dataset covering 10 warhammer unit type categories, served on Nyckel's own infrastructure — your image stays on Nyckel.
Send an image URL or file to the invoke endpoint; the response is a label with a confidence score.
Clone it, then correct predictions and add your own samples in the console — Nyckel retrains automatically, turning this into a custom model tuned to your data.
This function can be used to identify specific Warhammer unit types during gameplay, helping players make optimal strategic decisions. By quickly recognizing units, players can adapt their tactics in real-time to counter their opponents effectively.
Game organizers and analysts can utilize this function to evaluate the composition of armies in tournaments. By classifying unit types, they can provide insights into common strategies, helping players create more balanced lists.
Content creators can integrate this identifier into tools that generate reports, articles, or videos about different Warhammer units. By automating the classification process, they can streamline the creation of engaging content focused on unit strengths, weaknesses, and optimal uses.
Retail businesses can use this classification to manage their inventory by categorizing units. This helps in forecasting demand, creating targeted promotions, and optimizing stock levels for different types of Warhammer units.
Game developers can incorporate this function into training simulators to educate new players on unit types and their roles. By providing real-time classification, players can learn the intricacies of gameplay through hands-on experience.
AR applications can leverage this identifier to recognize Warhammer units in user environments, enhancing player interaction. It allows for dynamic overlays of information, such as stats and strategies, based on identified units during gameplay.
Developers can analyze usage data from classified units to assess gameplay balance. By understanding which unit types are favored and their win rates, adjustments can be made to ensure a more equitable and fun gaming experience.
A zero-shot classifier uses a large foundation model's general knowledge to pick between your labels — no task-specific training, so new or edited labels work immediately. A Nyckel-trained classifier has been trained on labeled examples and runs on Nyckel's own infrastructure, which typically makes it faster, cheaper per call, and more accurate on data that resembles its training set. The "Under the hood" section on this page shows which kind this classifier is, and any classifier can be adapted into a trained one by adding your own examples.
Honestly: we can't know in advance — it depends on your data stream and how closely it resembles what this classifier has seen. The reliable way to find out is to measure it on your own data: start invoking the classifier with real traffic, or upload and annotate a set of images in the console — make sure they look like your production data, not idealized examples. Nyckel's evaluation metrics then show you exactly how it performs on that data before you rely on it.
No classifier is perfect, so Nyckel is built around the correction loop: invokes can be captured for review, you confirm or correct predictions in the console, and corrections become training data. Over time the model adapts to your data distribution — accuracy on your traffic improves with use rather than staying fixed.
No. This warhammer unit type classifier works out of the box — clone it into your console and you'll have your own API endpoint in under a minute. Training data only enters the picture when you want to adapt it: your corrected predictions and uploaded samples improve the model, and you can also edit the label set to match your needs.
Trying the classifier on this page is free with no signup. Cloning it requires a free account, and the free tier covers your first API calls each month — see nyckel.com/pricing for current limits and paid tiers.
Add this pretrained classifier to your Nyckel console — you'll get a live API endpoint in under a minute, and a path to a custom model when you need one.