# Switti 1024

> Switti is a scale-wise transformer for fast text-to-image generation that outperforms existing T2I AR models and competes with state-of-the-art T2I diffusion models while being faster than distilled diffusion models.


## Overview

- **Endpoint**: `https://fal.run/fal-ai/switti`
- **Model ID**: `fal-ai/switti`
- **Category**: text-to-image
- **Kind**: inference


## 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:


- **`prompt`** (`string`, _required_):
  The prompt to generate an image from.
  - Examples: "A cat wearing a hoodie with 'FAL' written on it."

- **`negative_prompt`** (`string`, _optional_):
  The negative prompt to use. Use it to address details that you don't want
  in the image. This could be colors, objects, scenery and even the small details
  (e.g. moustache, blurry, low resolution). Default value: `""`
  - Default: `""`
  - Examples: ""

- **`sampling_top_k`** (`integer`, _optional_):
  The number of top-k tokens to sample from. Default value: `400`
  - Default: `400`
  - Range: `10` to `1000`

- **`sampling_top_p`** (`float`, _optional_):
  The top-p probability to sample from. Default value: `0.95`
  - Default: `0.95`
  - Range: `0.1` to `1`

- **`more_smooth`** (`boolean`, _optional_):
  Smoothing with Gumbel softmax sampling Default value: `true`
  - Default: `true`

- **`more_diverse`** (`boolean`, _optional_):
  More diverse sampling
  - Default: `false`

- **`smooth_start_si`** (`integer`, _optional_):
  Smoothing starting scale Default value: `2`
  - Default: `2`
  - Range: `0` to `10`

- **`turn_off_cfg_start_si`** (`integer`, _optional_):
  Disable CFG starting scale Default value: `8`
  - Default: `8`
  - Range: `0` to `10`

- **`last_scale_temp`** (`float`, _optional_):
  Temperature after disabling CFG Default value: `0.1`
  - Default: `0.1`
  - Range: `0.1` to `10`

- **`seed`** (`integer`, _optional_):
  The same seed and the same prompt given to the same version of the model
  will output the same image every time.

- **`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: `6`
  - Default: `6`
  - Range: `0` to `20`

- **`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`

- **`enable_safety_checker`** (`boolean`, _optional_):
  If set to true, the safety checker will be enabled. Default value: `true`
  - Default: `true`

- **`output_format`** (`OutputFormatEnum`, _optional_):
  The format of the generated image. Default value: `"jpeg"`
  - Default: `"jpeg"`
  - Options: `"jpeg"`, `"png"`



**Required Parameters Example**:

```json
{
  "prompt": "A cat wearing a hoodie with 'FAL' written on it."
}
```

**Full Example**:

```json
{
  "prompt": "A cat wearing a hoodie with 'FAL' written on it.",
  "negative_prompt": "",
  "sampling_top_k": 400,
  "sampling_top_p": 0.95,
  "more_smooth": true,
  "smooth_start_si": 2,
  "turn_off_cfg_start_si": 8,
  "last_scale_temp": 0.1,
  "guidance_scale": 6,
  "enable_safety_checker": true,
  "output_format": "jpeg"
}
```


### Output Schema

The API returns the following output format:

- **`images`** (`list<Image>`, _required_):
  The generated images
  - Array of Image
  - Examples: [{"height":1024,"content_type":"image/jpeg","url":"https://fal.media/files/lion/JpgBX7w379jHteLeeNsM5.jpeg","width":1024}]

- **`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<boolean>`, _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": [
    {
      "height": 1024,
      "content_type": "image/jpeg",
      "url": "https://fal.media/files/lion/JpgBX7w379jHteLeeNsM5.jpeg",
      "width": 1024
    }
  ],
  "prompt": ""
}
```


## Usage Examples

### cURL

```bash
curl --request POST \
  --url https://fal.run/fal-ai/switti \
  --header "Authorization: Key $FAL_KEY" \
  --header "Content-Type: application/json" \
  --data '{
     "prompt": "A cat wearing a hoodie with 'FAL' written on it."
   }'
```

### 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/switti",
    arguments={
        "prompt": "A cat wearing a hoodie with 'FAL' written on it."
    },
    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/switti", {
  input: {
    prompt: "A cat wearing a hoodie with 'FAL' written on it."
  },
  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/switti)
- [API Documentation](https://fal.ai/models/fal-ai/switti/api)
- [OpenAPI Schema](https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=fal-ai/switti)

### 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)