Segmind Tiny-SD (Portrait)
Convert text to images with the distilled stable diffusion model by Segmind, Small-SD. Segmind Small SD Serverless APIs, Segmind offers fastest deployment for Small-Stable-Diffusion inferences.
1import requests
2import json
3
4url = "https://api.segmind.com/v1/potraitsd1.5-txt2img"
5headers = {
6 "x-api-key": "YOUR_API_KEY",
7 "Content-Type": "application/json"
8}
9
10data = {
11 "prompt": "sample text",
12 "negative_prompt": "sample text",
13 "scheduler": "UniPC",
14 "num_inference_steps": 20,
15 "guidance_scale": 7.5,
16 "samples": 1,
17 "seed": -1,
18 "img_width": 512,
19 "img_height": 512,
20 "base64": false
21}
22
23response = requests.post(url, headers=headers, json=data)
24
25if response.status_code == 200:
26 result = response.json()
27 print(json.dumps(result, indent=2))
28else:
29 print(f"Error: {response.status_code}")
30 print(response.text)
1import requests
2import json
3
4url = "https://api.segmind.com/v1/potraitsd1.5-txt2img"
5headers = {
6 "x-api-key": "YOUR_API_KEY",
7 "Content-Type": "application/json"
8}
9
10data = {
11 "prompt": "sample text",
12 "negative_prompt": "sample text",
13 "scheduler": "UniPC",
14 "num_inference_steps": 20,
15 "guidance_scale": 7.5,
16 "samples": 1,
17 "seed": -1,
18 "img_width": 512,
19 "img_height": 512,
20 "base64": false
21}
22
23response = requests.post(url, headers=headers, json=data)
24
25if response.status_code == 200:
26 result = response.json()
27 print(json.dumps(result, indent=2))
28else:
29 print(f"Error: {response.status_code}")
30 print(response.text)
API Endpoint
https://api.segmind.com/v1/potraitsd1.5-txt2img
Parameters
prompt
requiredstring
Prompt to render
base64
optionalboolean
Base64 encoding of the output image.
false
guidance_scale
optionalnumber
Scale for classifier-free guidance
7.5
Range: 0.1 - 25img_height
optionalinteger
Height of the Image
512
512
768
1024
img_width
optionalinteger
Width of the image.
512
512
768
1024
negative_prompt
optionalstring
Prompts to exclude, eg. 'bad anatomy, bad hands, missing fingers'
num_inference_steps
optionalinteger
Number of denoising steps.
20
Range: 20 - 100samples
optionalinteger
Number of samples to generate.
1
Range: 1 - 4scheduler
optionalstring
Type of scheduler.
"UniPC"
"DDIM"
"DPM Multi"
"DPM Single"
"Euler a"
"Euler"
"Heun"
"DPM2 a Karras"
"DPM2 Karras"
"LMS"
"PNDM"
+2 moreseed
optionalinteger
Seed for image generation.
-1
Response Type
Returns: Text/JSON
Common Error Codes
The API returns standard HTTP status codes. Detailed error messages are provided in the response body.
Bad Request
Invalid parameters or request format
Unauthorized
Missing or invalid API key
Forbidden
Insufficient permissions
Not Found
Model or endpoint not found
Insufficient Credits
Not enough credits to process request
Rate Limited
Too many requests
Server Error
Internal server error
Bad Gateway
Service temporarily unavailable
Timeout
Request timed out