# Dreamshaper > Dreamshaper model. ## Overview - **Endpoint**: `https://fal.run/fal-ai/dreamshaper` - **Model ID**: `fal-ai/dreamshaper` - **Category**: text-to-image - **Kind**: inference **Tags**: stylized, diffusion ## Pricing - **Price**: $0 per compute seconds For more details, see [fal.ai pricing](https://fal.ai/pricing). ## API Information This model can be used via our HTTP API or more conveniently via our client libraries. See the input and output schema below, as well as the usage examples. ### Input Schema The API accepts the following input parameters: - **`model_name`** (`ModelNameEnum`, _optional_): The Dreamshaper model to use. - Options: `"Lykon/dreamshaper-xl-1-0"`, `"Lykon/dreamshaper-xl-v2-turbo"`, `"Lykon/dreamshaper-8"` - Examples: "Lykon/dreamshaper-8", "Lykon/dreamshaper-xl-1-0", "Lykon/dreamshaper-xl-v2-turbo" - **`prompt`** (`string`, _required_): The prompt to use for generating the image. Be as descriptive as possible for best results. - Examples: "A hyperdetailed photograph of a Cat dressed as a mafia boss holding a fish walking down a Japanese fish market with an angry face, 8k resolution, best quality, beautiful photograph, dynamic lighting," - **`negative_prompt`** (`string`, _optional_): The negative prompt to use. Use it to address details that you don't want in the image. Default value: `"(worst quality, low quality, normal quality, lowres, low details, oversaturated, undersaturated, overexposed, underexposed, grayscale, bw, bad photo, bad photography, bad art:1.4), (watermark, signature, text font, username, error, logo, words, letters, digits, autograph, trademark, name:1.2), (blur, blurry, grainy), morbid, ugly, asymmetrical, mutated malformed, mutilated, poorly lit, bad shadow, draft, cropped, out of frame, cut off, censored, jpeg artifacts, out of focus, glitch, duplicate, (airbrushed, cartoon, anime, semi-realistic, cgi, render, blender, digital art, manga, amateur:1.3), (3D ,3D Game, 3D Game Scene, 3D Character:1.1), (bad hands, bad anatomy, bad body, bad face, bad teeth, bad arms, bad legs, deformities:1.3)"` - Default: `"(worst quality, low quality, normal quality, lowres, low details, oversaturated, undersaturated, overexposed, underexposed, grayscale, bw, bad photo, bad photography, bad art:1.4), (watermark, signature, text font, username, error, logo, words, letters, digits, autograph, trademark, name:1.2), (blur, blurry, grainy), morbid, ugly, asymmetrical, mutated malformed, mutilated, poorly lit, bad shadow, draft, cropped, out of frame, cut off, censored, jpeg artifacts, out of focus, glitch, duplicate, (airbrushed, cartoon, anime, semi-realistic, cgi, render, blender, digital art, manga, amateur:1.3), (3D ,3D Game, 3D Game Scene, 3D Character:1.1), (bad hands, bad anatomy, bad body, bad face, bad teeth, bad arms, bad legs, deformities:1.3)"` - **`image_size`** (`ImageSize | Enum`, _optional_) - Default: `{"height":1024,"width":1024}` - One of: ImageSize | Enum - **`num_inference_steps`** (`integer`, _optional_): The number of inference steps to perform. Default value: `35` - Default: `35` - Range: `1` to `70` - **`guidance_scale`** (`float`, _optional_): The CFG (Classifier Free Guidance) scale is a measure of how close you want the model to stick to your prompt when looking for a related image to show you. Default value: `5` - Default: `5` - Range: `0` to `20` - **`loras`** (`list`, _optional_): The list of LoRA weights to use. - Default: `[]` - Array of LoraWeight - **`embeddings`** (`list`, _optional_): The list of embeddings to use. - Default: `[]` - Array of Embedding - **`expand_prompt`** (`boolean`, _optional_): If set to true, the prompt will be expanded with additional prompts. - Default: `false` - **`num_images`** (`integer`, _optional_): The number of images to generate. Default value: `1` - Default: `1` - Range: `1` to `8` - **`seed`** (`integer`, _optional_): The same seed and the same prompt given to the same version of Stable Diffusion will output the same image every time. - **`enable_safety_checker`** (`boolean`, _optional_): If set to true, the safety checker will be enabled. Default value: `true` - Default: `true` - **`sync_mode`** (`boolean`, _optional_): If set to true, the function will wait for the image to be generated and uploaded before returning the response. This will increase the latency of the function but it allows you to get the image directly in the response without going through the CDN. - Default: `false` - **`format`** (`FormatEnum`, _optional_): The format of the generated image. Default value: `"jpeg"` - Default: `"jpeg"` - Options: `"jpeg"`, `"png"` - **`safety_checker_version`** (`SafetyCheckerVersionEnum`, _optional_): The version of the safety checker to use. v1 is the default CompVis safety checker. v2 uses a custom ViT model. Default value: `"v1"` - Default: `"v1"` - Options: `"v1"`, `"v2"` **Required Parameters Example**: ```json { "prompt": "A hyperdetailed photograph of a Cat dressed as a mafia boss holding a fish walking down a Japanese fish market with an angry face, 8k resolution, best quality, beautiful photograph, dynamic lighting," } ``` **Full Example**: ```json { "model_name": "Lykon/dreamshaper-8", "prompt": "A hyperdetailed photograph of a Cat dressed as a mafia boss holding a fish walking down a Japanese fish market with an angry face, 8k resolution, best quality, beautiful photograph, dynamic lighting,", "negative_prompt": "(worst quality, low quality, normal quality, lowres, low details, oversaturated, undersaturated, overexposed, underexposed, grayscale, bw, bad photo, bad photography, bad art:1.4), (watermark, signature, text font, username, error, logo, words, letters, digits, autograph, trademark, name:1.2), (blur, blurry, grainy), morbid, ugly, asymmetrical, mutated malformed, mutilated, poorly lit, bad shadow, draft, cropped, out of frame, cut off, censored, jpeg artifacts, out of focus, glitch, duplicate, (airbrushed, cartoon, anime, semi-realistic, cgi, render, blender, digital art, manga, amateur:1.3), (3D ,3D Game, 3D Game Scene, 3D Character:1.1), (bad hands, bad anatomy, bad body, bad face, bad teeth, bad arms, bad legs, deformities:1.3)", "image_size": { "height": 1024, "width": 1024 }, "num_inference_steps": 35, "guidance_scale": 5, "loras": [], "embeddings": [], "num_images": 1, "enable_safety_checker": true, "format": "jpeg", "safety_checker_version": "v1" } ``` ### Output Schema The API returns the following output format: - **`images`** (`list`, _required_): The generated image files info. - Array of Image - **`timings`** (`Timings`, _required_) - **`seed`** (`integer`, _required_): Seed of the generated Image. It will be the same value of the one passed in the input or the randomly generated that was used in case none was passed. - **`has_nsfw_concepts`** (`list`, _required_): Whether the generated images contain NSFW concepts. - Array of boolean - **`prompt`** (`string`, _required_): The prompt used for generating the image. **Example Response**: ```json { "images": [ { "url": "", "content_type": "image/jpeg" } ], "prompt": "" } ``` ## Usage Examples ### cURL ```bash curl --request POST \ --url https://fal.run/fal-ai/dreamshaper \ --header "Authorization: Key $FAL_KEY" \ --header "Content-Type: application/json" \ --data '{ "prompt": "A hyperdetailed photograph of a Cat dressed as a mafia boss holding a fish walking down a Japanese fish market with an angry face, 8k resolution, best quality, beautiful photograph, dynamic lighting," }' ``` ### Python Ensure you have the Python client installed: ```bash pip install fal-client ``` Then use the API client to make requests: ```python import fal_client def on_queue_update(update): if isinstance(update, fal_client.InProgress): for log in update.logs: print(log["message"]) result = fal_client.subscribe( "fal-ai/dreamshaper", arguments={ "prompt": "A hyperdetailed photograph of a Cat dressed as a mafia boss holding a fish walking down a Japanese fish market with an angry face, 8k resolution, best quality, beautiful photograph, dynamic lighting," }, with_logs=True, on_queue_update=on_queue_update, ) print(result) ``` ### JavaScript Ensure you have the JavaScript client installed: ```bash npm install --save @fal-ai/client ``` Then use the API client to make requests: ```javascript import { fal } from "@fal-ai/client"; const result = await fal.subscribe("fal-ai/dreamshaper", { input: { prompt: "A hyperdetailed photograph of a Cat dressed as a mafia boss holding a fish walking down a Japanese fish market with an angry face, 8k resolution, best quality, beautiful photograph, dynamic lighting," }, logs: true, onQueueUpdate: (update) => { if (update.status === "IN_PROGRESS") { update.logs.map((log) => log.message).forEach(console.log); } }, }); console.log(result.data); console.log(result.requestId); ``` ## Additional Resources ### Documentation - [Model Playground](https://fal.ai/models/fal-ai/dreamshaper) - [API Documentation](https://fal.ai/models/fal-ai/dreamshaper/api) - [OpenAPI Schema](https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=fal-ai/dreamshaper) ### fal.ai Platform - [Platform Documentation](https://docs.fal.ai) - [Python Client](https://docs.fal.ai/clients/python) - [JavaScript Client](https://docs.fal.ai/clients/javascript)