Name: Text to Image
Rating: 4.4 (4431 reviews)

Text to Image

Generate an image based on a given text prompt.

For more details about the text-to-image task, check out its dedicated page! You will find examples and related materials.

Recommended models

black-forest-labs/FLUX.1-dev: One of the most powerful image generation models that can generate realistic outputs.
Kwai-Kolors/Kolors: Text-to-image model for photorealistic generation.
stabilityai/stable-diffusion-3-medium-diffusers: A powerful text-to-image model.

Explore all available models and find the one that suits you best here.

Using the API

Language

Client

Provider

Settings

from huggingface_hub import InferenceClient client = InferenceClient( provider="fal-ai", api_key="hf_xxxxxxxxxxxxxxxxxxxxxxxx", ) # output is a PIL.Image object image = client.text_to_image( "Astronaut riding a horse", model="black-forest-labs/FLUX.1-dev", )

API specification

Request

Headers
authorization	string	Authentication header in the form `'Bearer: hf_**'` when `hf_**` is a personal user access token with “Inference Providers” permission. You can generate one from your settings page.

Payload
inputs*	string	The input text data (sometimes called “prompt”)
parameters	object
guidance_scale	number	A higher guidance scale value encourages the model to generate images closely linked to the text prompt, but values too high may cause saturation and other artifacts.
negative_prompt	string	One prompt to guide what NOT to include in image generation.
num_inference_steps	integer	The number of denoising steps. More denoising steps usually lead to a higher quality image at the expense of slower inference.
width	integer	The width in pixels of the output image
height	integer	The height in pixels of the output image
scheduler	string	Override the scheduler with a compatible one.
seed	integer	Seed for the random number generator.

Response

Body
image	unknown	The generated image returned as raw bytes in the payload.

<>Update on GitHub