Midjourney V7

103
10
5.0B
2 languages
—
by
Kvikontent
Image Model
OTHER
5B params
New
103 downloads
Early-stage
Try on Hugging FaceAdd to Compare
Edge AI:
Mobile
Laptop
Server
12GB+ RAM
Mobile
Laptop
Server
Quick Summary

Midjourney is most realistic and powerful ai image generator in the world.

Device Compatibility

Mobile
4-6GB RAM
Laptop
16GB RAM
Server
GPU
Minimum Recommended
5GB+ RAM

Code Examples

Examplespython
import requests

API_URL = "https://api-inference.huggingface.co/models/Kvikontent/midjourney-v7"
headers = {"Authorization": "Bearer HUGGINGFACE_API_TOKEN"}

def query(payload):
	response = requests.post(API_URL, headers=headers, json=payload)
	return response.content
image_bytes = query({
	"inputs": "Astronaut riding a horse",
})
# You can access the image with PIL.Image for example
import io
from PIL import Image
image = Image.open(io.BytesIO(image_bytes))
Examplespython
import requests

API_URL = "https://api-inference.huggingface.co/models/Kvikontent/midjourney-v7"
headers = {"Authorization": "Bearer HUGGINGFACE_API_TOKEN"}

def query(payload):
	response = requests.post(API_URL, headers=headers, json=payload)
	return response.content
image_bytes = query({
	"inputs": "Astronaut riding a horse",
})
# You can access the image with PIL.Image for example
import io
from PIL import Image
image = Image.open(io.BytesIO(image_bytes))
Examplespython
import requests

API_URL = "https://api-inference.huggingface.co/models/Kvikontent/midjourney-v7"
headers = {"Authorization": "Bearer HUGGINGFACE_API_TOKEN"}

def query(payload):
	response = requests.post(API_URL, headers=headers, json=payload)
	return response.content
image_bytes = query({
	"inputs": "Astronaut riding a horse",
})
# You can access the image with PIL.Image for example
import io
from PIL import Image
image = Image.open(io.BytesIO(image_bytes))
Examplespython
import requests

API_URL = "https://api-inference.huggingface.co/models/Kvikontent/midjourney-v7"
headers = {"Authorization": "Bearer HUGGINGFACE_API_TOKEN"}

def query(payload):
	response = requests.post(API_URL, headers=headers, json=payload)
	return response.content
image_bytes = query({
	"inputs": "Astronaut riding a horse",
})
# You can access the image with PIL.Image for example
import io
from PIL import Image
image = Image.open(io.BytesIO(image_bytes))
Examplespython
import requests

API_URL = "https://api-inference.huggingface.co/models/Kvikontent/midjourney-v7"
headers = {"Authorization": "Bearer HUGGINGFACE_API_TOKEN"}

def query(payload):
	response = requests.post(API_URL, headers=headers, json=payload)
	return response.content
image_bytes = query({
	"inputs": "Astronaut riding a horse",
})
# You can access the image with PIL.Image for example
import io
from PIL import Image
image = Image.open(io.BytesIO(image_bytes))
Examplespython
import requests

API_URL = "https://api-inference.huggingface.co/models/Kvikontent/midjourney-v7"
headers = {"Authorization": "Bearer HUGGINGFACE_API_TOKEN"}

def query(payload):
	response = requests.post(API_URL, headers=headers, json=payload)
	return response.content
image_bytes = query({
	"inputs": "Astronaut riding a horse",
})
# You can access the image with PIL.Image for example
import io
from PIL import Image
image = Image.open(io.BytesIO(image_bytes))

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