Reference ResNet-50 trained on ImageNet-1K. Useful baseline for vision pipelines.
ResNet-50 (microsoft/resnet-50) is a vision model from Microsoft. Context window: — tokens; max output —. Pricing via AIgateway: $0.0002 per image. Call it via https://api.aigateway.sh/v1/chat/completions with the OpenAI SDK — set model="microsoft/resnet-50". Best for: ImageNet classification, Image tagging baselines.
curl https://api.aigateway.sh/v1/chat/completions \
-H "Authorization: Bearer $AIGATEWAY_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"microsoft/resnet-50","messages":[{"role":"user","content":"hello"}],"stream":true}'{
"model": "microsoft/resnet-50",
"messages": [
{ "role": "system", "content": "You are a helpful assistant." },
{ "role": "user", "content": "Hello!" }
],
"temperature": 0.7,
"top_p": 0.95,
"max_tokens": 1024,
"stream": false
}{
"id": "chatcmpl-abc123",
"object": "chat.completion",
"created": 1776947082,
"model": "microsoft/resnet-50",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "Hello! How can I help you today?"
},
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 24,
"completion_tokens": 12,
"total_tokens": 36
}
}# pip install aigateway-py openai
# aigateway-py adds sub-accounts, evals, replays, jobs, webhook verify.
# openai SDK covers chat — drop-in per our SDK's own guidance.
from openai import OpenAI
client = OpenAI(
base_url="https://api.aigateway.sh/v1",
api_key="sk-aig-...",
)
r = client.chat.completions.create(
model="microsoft/resnet-50",
messages=[{"role": "user", "content": "Hello!"}],
)
print(r.choices[0].message.content)