Prediction

fofr/ays-text-to-image:a004c3ac

Model

fofr/ays-text-to-image:a004c3ac

ID

5enrvraw95rgm0cf5veva7rggm

Status

Succeeded

Source

Web

Hardware

A40

Total duration

12.4s

Created

11 months ago

Input

steps: 10
width: 1156
height: 768
prompt: a photo of some steps
checkpoint: ProteusV0.4.safetensors
num_outputs: 1
sampler_name: euler
output_format: webp
guidance_scale: 7.5
output_quality: 80
negative_prompt

{
  "steps": 10,
  "width": 1156,
  "height": 768,
  "prompt": "a photo of some steps",
  "checkpoint": "ProteusV0.4.safetensors",
  "num_outputs": 1,
  "sampler_name": "euler",
  "output_format": "webp",
  "guidance_scale": 7.5,
  "output_quality": 80,
  "negative_prompt": ""
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run fofr/ays-text-to-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/ays-text-to-image:a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e",
  {
    input: {
      steps: 10,
      width: 1156,
      height: 768,
      prompt: "a photo of some steps",
      checkpoint: "ProteusV0.4.safetensors",
      num_outputs: 1,
      sampler_name: "euler",
      output_format: "webp",
      guidance_scale: 7.5,
      output_quality: 80,
      negative_prompt: ""
    }
  }
);
console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run fofr/ays-text-to-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/ays-text-to-image:a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e",
    input={
        "steps": 10,
        "width": 1156,
        "height": 768,
        "prompt": "a photo of some steps",
        "checkpoint": "ProteusV0.4.safetensors",
        "num_outputs": 1,
        "sampler_name": "euler",
        "output_format": "webp",
        "guidance_scale": 7.5,
        "output_quality": 80,
        "negative_prompt": ""
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run fofr/ays-text-to-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e",
    "input": {
      "steps": 10,
      "width": 1156,
      "height": 768,
      "prompt": "a photo of some steps",
      "checkpoint": "ProteusV0.4.safetensors",
      "num_outputs": 1,
      "sampler_name": "euler",
      "output_format": "webp",
      "guidance_scale": 7.5,
      "output_quality": 80,
      "negative_prompt": ""
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/fofr/ays-text-to-image@sha256:a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e \
  -i 'steps=10' \
  -i 'width=1156' \
  -i 'height=768' \
  -i 'prompt="a photo of some steps"' \
  -i 'checkpoint="ProteusV0.4.safetensors"' \
  -i 'num_outputs=1' \
  -i 'sampler_name="euler"' \
  -i 'output_format="webp"' \
  -i 'guidance_scale=7.5' \
  -i 'output_quality=80' \
  -i 'negative_prompt=""'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/fofr/ays-text-to-image@sha256:a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "steps": 10,
      "width": 1156,
      "height": 768,
      "prompt": "a photo of some steps",
      "checkpoint": "ProteusV0.4.safetensors",
      "num_outputs": 1,
      "sampler_name": "euler",
      "output_format": "webp",
      "guidance_scale": 7.5,
      "output_quality": 80,
      "negative_prompt": ""
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

{
  "completed_at": "2024-04-30T11:57:02.551140Z",
  "created_at": "2024-04-30T11:56:50.121000Z",
  "data_removed": false,
  "error": null,
  "id": "5enrvraw95rgm0cf5veva7rggm",
  "input": {
    "steps": 10,
    "width": 1156,
    "height": 768,
    "prompt": "a photo of some steps",
    "checkpoint": "ProteusV0.4.safetensors",
    "num_outputs": 1,
    "sampler_name": "euler",
    "output_format": "webp",
    "guidance_scale": 7.5,
    "output_quality": 80,
    "negative_prompt": ""
  },
  "logs": "Random seed set to: 2615771573\nChecking inputs\n====================================\nChecking weights\n⏳ Downloading ProteusV0.4.safetensors to ComfyUI/models/checkpoints\n⌛️ Downloaded ProteusV0.4.safetensors in 7.46s, size: 6617.77MB\n✅ ProteusV0.4.safetensors\n====================================\nRunning workflow\ngot prompt\nExecuting node 4, title: Load Checkpoint, class type: CheckpointLoaderSimple\nmodel_type EPS\nUsing pytorch attention in VAE\nUsing pytorch attention in VAE\nclip missing: ['clip_l.logit_scale', 'clip_l.transformer.text_projection.weight']\nloaded straight to GPU\nRequested to load SDXL\nLoading 1 new model\nExecuting node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nRequested to load SDXLClipModel\nLoading 1 new model\nExecuting node 19, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nExecuting node 21, title: SamplerCustom, class type: SamplerCustom\n  0%|          | 0/10 [00:00<?, ?it/s]\n 20%|██        | 2/10 [00:00<00:00,  8.88it/s]\n 30%|███       | 3/10 [00:00<00:00,  7.63it/s]\n 40%|████      | 4/10 [00:00<00:00,  7.13it/s]\n 50%|█████     | 5/10 [00:00<00:00,  6.87it/s]\n 60%|██████    | 6/10 [00:00<00:00,  6.72it/s]\n 70%|███████   | 7/10 [00:01<00:00,  6.59it/s]\n 80%|████████  | 8/10 [00:01<00:00,  6.53it/s]\n 90%|█████████ | 9/10 [00:01<00:00,  6.49it/s]\n100%|██████████| 10/10 [00:01<00:00,  6.47it/s]\n100%|██████████| 10/10 [00:01<00:00,  6.78it/s]\nRequested to load AutoencoderKL\nLoading 1 new model\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 9, title: Save Image, class type: SaveImage\nPrompt executed in 4.16 seconds\noutputs:  {'9': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nContents of /tmp/outputs:\nComfyUI_00001_.png",
  "metrics": {
    "predict_time": 12.400336,
    "total_time": 12.43014
  },
  "output": [
    "https://replicate.delivery/pbxt/HV02s0HiY9JfJCwavsHeeeypu1rphkf56lpi2HqvVtftjO6rE/ComfyUI_00001_.webp"
  ],
  "started_at": "2024-04-30T11:56:50.150804Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/5enrvraw95rgm0cf5veva7rggm",
    "cancel": "https://api.replicate.com/v1/predictions/5enrvraw95rgm0cf5veva7rggm/cancel"
  },
  "version": "a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e"
}

Generated in

12.4 seconds

Tweak it ShareReport

Prediction

fofr/ays-text-to-image:a004c3ac

Model

fofr/ays-text-to-image:a004c3ac

ID

v0mctz9t49rgp0cf5vf984jc10

Status

Succeeded

Source

Web

Hardware

A40

Total duration

2.6s

Created

11 months ago

Input

steps: 10
width: 1156
height: 768
prompt: a beautiful portrait photo of a cat
checkpoint: ProteusV0.4.safetensors
num_outputs: 1
sampler_name: euler
output_format: webp
guidance_scale: 7.5
output_quality: 80
negative_prompt

{
  "steps": 10,
  "width": 1156,
  "height": 768,
  "prompt": "a beautiful portrait photo of a cat",
  "checkpoint": "ProteusV0.4.safetensors",
  "num_outputs": 1,
  "sampler_name": "euler",
  "output_format": "webp",
  "guidance_scale": 7.5,
  "output_quality": 80,
  "negative_prompt": ""
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run fofr/ays-text-to-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/ays-text-to-image:a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e",
  {
    input: {
      steps: 10,
      width: 1156,
      height: 768,
      prompt: "a beautiful portrait photo of a cat",
      checkpoint: "ProteusV0.4.safetensors",
      num_outputs: 1,
      sampler_name: "euler",
      output_format: "webp",
      guidance_scale: 7.5,
      output_quality: 80,
      negative_prompt: ""
    }
  }
);
console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run fofr/ays-text-to-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/ays-text-to-image:a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e",
    input={
        "steps": 10,
        "width": 1156,
        "height": 768,
        "prompt": "a beautiful portrait photo of a cat",
        "checkpoint": "ProteusV0.4.safetensors",
        "num_outputs": 1,
        "sampler_name": "euler",
        "output_format": "webp",
        "guidance_scale": 7.5,
        "output_quality": 80,
        "negative_prompt": ""
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run fofr/ays-text-to-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e",
    "input": {
      "steps": 10,
      "width": 1156,
      "height": 768,
      "prompt": "a beautiful portrait photo of a cat",
      "checkpoint": "ProteusV0.4.safetensors",
      "num_outputs": 1,
      "sampler_name": "euler",
      "output_format": "webp",
      "guidance_scale": 7.5,
      "output_quality": 80,
      "negative_prompt": ""
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/fofr/ays-text-to-image@sha256:a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e \
  -i 'steps=10' \
  -i 'width=1156' \
  -i 'height=768' \
  -i 'prompt="a beautiful portrait photo of a cat"' \
  -i 'checkpoint="ProteusV0.4.safetensors"' \
  -i 'num_outputs=1' \
  -i 'sampler_name="euler"' \
  -i 'output_format="webp"' \
  -i 'guidance_scale=7.5' \
  -i 'output_quality=80' \
  -i 'negative_prompt=""'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/fofr/ays-text-to-image@sha256:a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "steps": 10,
      "width": 1156,
      "height": 768,
      "prompt": "a beautiful portrait photo of a cat",
      "checkpoint": "ProteusV0.4.safetensors",
      "num_outputs": 1,
      "sampler_name": "euler",
      "output_format": "webp",
      "guidance_scale": 7.5,
      "output_quality": 80,
      "negative_prompt": ""
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

{
  "completed_at": "2024-04-30T11:57:49.561613Z",
  "created_at": "2024-04-30T11:57:46.914000Z",
  "data_removed": false,
  "error": null,
  "id": "v0mctz9t49rgp0cf5vf984jc10",
  "input": {
    "steps": 10,
    "width": 1156,
    "height": 768,
    "prompt": "a beautiful portrait photo of a cat",
    "checkpoint": "ProteusV0.4.safetensors",
    "num_outputs": 1,
    "sampler_name": "euler",
    "output_format": "webp",
    "guidance_scale": 7.5,
    "output_quality": 80,
    "negative_prompt": ""
  },
  "logs": "Random seed set to: 2253141809\nChecking inputs\n====================================\nChecking weights\n✅ ProteusV0.4.safetensors\n====================================\nRunning workflow\ngot prompt\nExecuting node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nExecuting node 21, title: SamplerCustom, class type: SamplerCustom\n  0%|          | 0/10 [00:00<?, ?it/s]\n 20%|██        | 2/10 [00:00<00:00,  8.87it/s]\n 30%|███       | 3/10 [00:00<00:00,  7.62it/s]\n 40%|████      | 4/10 [00:00<00:00,  7.12it/s]\n 50%|█████     | 5/10 [00:00<00:00,  6.86it/s]\n 60%|██████    | 6/10 [00:00<00:00,  6.71it/s]\n 70%|███████   | 7/10 [00:01<00:00,  6.60it/s]\n 80%|████████  | 8/10 [00:01<00:00,  6.54it/s]\n 90%|█████████ | 9/10 [00:01<00:00,  6.50it/s]\n100%|██████████| 10/10 [00:01<00:00,  6.47it/s]\n100%|██████████| 10/10 [00:01<00:00,  6.78it/s]\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 9, title: Save Image, class type: SaveImage\nPrompt executed in 1.93 seconds\noutputs:  {'9': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nContents of /tmp/outputs:\nComfyUI_00001_.png",
  "metrics": {
    "predict_time": 2.640387,
    "total_time": 2.647613
  },
  "output": [
    "https://replicate.delivery/pbxt/iFAVZOMyKxJmDhOiyYTLFBBrG9M1TTlJl9Ye2KprPu2e6ovSA/ComfyUI_00001_.webp"
  ],
  "started_at": "2024-04-30T11:57:46.921226Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/v0mctz9t49rgp0cf5vf984jc10",
    "cancel": "https://api.replicate.com/v1/predictions/v0mctz9t49rgp0cf5vf984jc10/cancel"
  },
  "version": "a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e"
}

Generated in

2.6 seconds

Tweak it ShareReport

Prediction

fofr/ays-text-to-image:a004c3ac

Model

fofr/ays-text-to-image:a004c3ac

ID

n81g2exv6hrgm0cf5vftvh1r38

Status

Succeeded

Source

Web

Hardware

A40

Total duration

2.4s

Created

11 months ago

Input

steps: 10
width: 1156
height: 768
prompt: a closeup of a cute 3d character in a forest
checkpoint: pixlAnimeCartoonComic_v10.safetensors
num_outputs: 1
sampler_name: euler
output_format: webp
guidance_scale: 7.5
output_quality: 80
negative_prompt

{
  "steps": 10,
  "width": 1156,
  "height": 768,
  "prompt": "a closeup of a cute 3d character in a forest",
  "checkpoint": "pixlAnimeCartoonComic_v10.safetensors",
  "num_outputs": 1,
  "sampler_name": "euler",
  "output_format": "webp",
  "guidance_scale": 7.5,
  "output_quality": 80,
  "negative_prompt": ""
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run fofr/ays-text-to-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/ays-text-to-image:a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e",
  {
    input: {
      steps: 10,
      width: 1156,
      height: 768,
      prompt: "a closeup of a cute 3d character in a forest",
      checkpoint: "pixlAnimeCartoonComic_v10.safetensors",
      num_outputs: 1,
      sampler_name: "euler",
      output_format: "webp",
      guidance_scale: 7.5,
      output_quality: 80,
      negative_prompt: ""
    }
  }
);
console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run fofr/ays-text-to-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/ays-text-to-image:a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e",
    input={
        "steps": 10,
        "width": 1156,
        "height": 768,
        "prompt": "a closeup of a cute 3d character in a forest",
        "checkpoint": "pixlAnimeCartoonComic_v10.safetensors",
        "num_outputs": 1,
        "sampler_name": "euler",
        "output_format": "webp",
        "guidance_scale": 7.5,
        "output_quality": 80,
        "negative_prompt": ""
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run fofr/ays-text-to-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e",
    "input": {
      "steps": 10,
      "width": 1156,
      "height": 768,
      "prompt": "a closeup of a cute 3d character in a forest",
      "checkpoint": "pixlAnimeCartoonComic_v10.safetensors",
      "num_outputs": 1,
      "sampler_name": "euler",
      "output_format": "webp",
      "guidance_scale": 7.5,
      "output_quality": 80,
      "negative_prompt": ""
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/fofr/ays-text-to-image@sha256:a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e \
  -i 'steps=10' \
  -i 'width=1156' \
  -i 'height=768' \
  -i 'prompt="a closeup of a cute 3d character in a forest"' \
  -i 'checkpoint="pixlAnimeCartoonComic_v10.safetensors"' \
  -i 'num_outputs=1' \
  -i 'sampler_name="euler"' \
  -i 'output_format="webp"' \
  -i 'guidance_scale=7.5' \
  -i 'output_quality=80' \
  -i 'negative_prompt=""'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/fofr/ays-text-to-image@sha256:a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "steps": 10,
      "width": 1156,
      "height": 768,
      "prompt": "a closeup of a cute 3d character in a forest",
      "checkpoint": "pixlAnimeCartoonComic_v10.safetensors",
      "num_outputs": 1,
      "sampler_name": "euler",
      "output_format": "webp",
      "guidance_scale": 7.5,
      "output_quality": 80,
      "negative_prompt": ""
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

{
  "completed_at": "2024-04-30T11:59:27.882458Z",
  "created_at": "2024-04-30T11:59:25.492000Z",
  "data_removed": false,
  "error": null,
  "id": "n81g2exv6hrgm0cf5vftvh1r38",
  "input": {
    "steps": 10,
    "width": 1156,
    "height": 768,
    "prompt": "a closeup of a cute 3d character in a forest",
    "checkpoint": "pixlAnimeCartoonComic_v10.safetensors",
    "num_outputs": 1,
    "sampler_name": "euler",
    "output_format": "webp",
    "guidance_scale": 7.5,
    "output_quality": 80,
    "negative_prompt": ""
  },
  "logs": "Random seed set to: 124553089\nChecking inputs\n====================================\nChecking weights\n✅ pixlAnimeCartoonComic_v10.safetensors\n====================================\nRunning workflow\ngot prompt\nExecuting node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nExecuting node 21, title: SamplerCustom, class type: SamplerCustom\n  0%|          | 0/10 [00:00<?, ?it/s]\n 20%|██        | 2/10 [00:00<00:00,  8.92it/s]\n 30%|███       | 3/10 [00:00<00:00,  7.68it/s]\n 40%|████      | 4/10 [00:00<00:00,  7.17it/s]\n 50%|█████     | 5/10 [00:00<00:00,  6.90it/s]\n 60%|██████    | 6/10 [00:00<00:00,  6.75it/s]\n 70%|███████   | 7/10 [00:01<00:00,  6.64it/s]\n 80%|████████  | 8/10 [00:01<00:00,  6.58it/s]\n 90%|█████████ | 9/10 [00:01<00:00,  6.54it/s]\n100%|██████████| 10/10 [00:01<00:00,  6.50it/s]\n100%|██████████| 10/10 [00:01<00:00,  6.82it/s]\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 9, title: Save Image, class type: SaveImage\nPrompt executed in 1.90 seconds\noutputs:  {'9': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nContents of /tmp/outputs:\nComfyUI_00001_.png",
  "metrics": {
    "predict_time": 2.381287,
    "total_time": 2.390458
  },
  "output": [
    "https://replicate.delivery/pbxt/p8KhNAfLffAfdRRdOP4EBNRnrPee2bOBZfw7B5ocYA9nPeovSA/ComfyUI_00001_.webp"
  ],
  "started_at": "2024-04-30T11:59:25.501171Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/n81g2exv6hrgm0cf5vftvh1r38",
    "cancel": "https://api.replicate.com/v1/predictions/n81g2exv6hrgm0cf5vftvh1r38/cancel"
  },
  "version": "a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e"
}

Generated in

2.4 seconds

Tweak it ShareReport

Prediction

fofr/ays-text-to-image:a004c3ac

Model

fofr/ays-text-to-image:a004c3ac

ID

em57nhsk2srgp0cf5vgtdjjg4g

Status

Succeeded

Source

Web

Hardware

A40

Total duration

2.4s

Created

11 months ago

Input

steps: 10
width: 1156
height: 768
prompt: a macro photo, dew drops
checkpoint: RealVisXL_V4.0.safetensors
num_outputs: 1
sampler_name: euler
output_format: webp
guidance_scale: 7.5
output_quality: 80

{
  "steps": 10,
  "width": 1156,
  "height": 768,
  "prompt": "a macro photo, dew drops",
  "checkpoint": "RealVisXL_V4.0.safetensors",
  "num_outputs": 1,
  "sampler_name": "euler",
  "output_format": "webp",
  "guidance_scale": 7.5,
  "output_quality": 80
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run fofr/ays-text-to-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/ays-text-to-image:a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e",
  {
    input: {
      steps: 10,
      width: 1156,
      height: 768,
      prompt: "a macro photo, dew drops",
      checkpoint: "RealVisXL_V4.0.safetensors",
      num_outputs: 1,
      sampler_name: "euler",
      output_format: "webp",
      guidance_scale: 7.5,
      output_quality: 80
    }
  }
);
console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run fofr/ays-text-to-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/ays-text-to-image:a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e",
    input={
        "steps": 10,
        "width": 1156,
        "height": 768,
        "prompt": "a macro photo, dew drops",
        "checkpoint": "RealVisXL_V4.0.safetensors",
        "num_outputs": 1,
        "sampler_name": "euler",
        "output_format": "webp",
        "guidance_scale": 7.5,
        "output_quality": 80
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run fofr/ays-text-to-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e",
    "input": {
      "steps": 10,
      "width": 1156,
      "height": 768,
      "prompt": "a macro photo, dew drops",
      "checkpoint": "RealVisXL_V4.0.safetensors",
      "num_outputs": 1,
      "sampler_name": "euler",
      "output_format": "webp",
      "guidance_scale": 7.5,
      "output_quality": 80
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/fofr/ays-text-to-image@sha256:a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e \
  -i 'steps=10' \
  -i 'width=1156' \
  -i 'height=768' \
  -i 'prompt="a macro photo, dew drops"' \
  -i 'checkpoint="RealVisXL_V4.0.safetensors"' \
  -i 'num_outputs=1' \
  -i 'sampler_name="euler"' \
  -i 'output_format="webp"' \
  -i 'guidance_scale=7.5' \
  -i 'output_quality=80'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/fofr/ays-text-to-image@sha256:a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "steps": 10,
      "width": 1156,
      "height": 768,
      "prompt": "a macro photo, dew drops",
      "checkpoint": "RealVisXL_V4.0.safetensors",
      "num_outputs": 1,
      "sampler_name": "euler",
      "output_format": "webp",
      "guidance_scale": 7.5,
      "output_quality": 80
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

{
  "completed_at": "2024-04-30T12:01:04.090920Z",
  "created_at": "2024-04-30T12:01:01.718000Z",
  "data_removed": false,
  "error": null,
  "id": "em57nhsk2srgp0cf5vgtdjjg4g",
  "input": {
    "steps": 10,
    "width": 1156,
    "height": 768,
    "prompt": "a macro photo, dew drops",
    "checkpoint": "RealVisXL_V4.0.safetensors",
    "num_outputs": 1,
    "sampler_name": "euler",
    "output_format": "webp",
    "guidance_scale": 7.5,
    "output_quality": 80
  },
  "logs": "Random seed set to: 309328795\nChecking inputs\n====================================\nChecking weights\n✅ RealVisXL_V4.0.safetensors\n====================================\nRunning workflow\ngot prompt\nExecuting node 21, title: SamplerCustom, class type: SamplerCustom\n  0%|          | 0/10 [00:00<?, ?it/s]\n 20%|██        | 2/10 [00:00<00:00,  8.81it/s]\n 30%|███       | 3/10 [00:00<00:00,  7.60it/s]\n 40%|████      | 4/10 [00:00<00:00,  7.11it/s]\n 50%|█████     | 5/10 [00:00<00:00,  6.85it/s]\n 60%|██████    | 6/10 [00:00<00:00,  6.69it/s]\n 70%|███████   | 7/10 [00:01<00:00,  6.59it/s]\n 80%|████████  | 8/10 [00:01<00:00,  6.53it/s]\n 90%|█████████ | 9/10 [00:01<00:00,  6.49it/s]\n100%|██████████| 10/10 [00:01<00:00,  6.45it/s]\n100%|██████████| 10/10 [00:01<00:00,  6.77it/s]\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 9, title: Save Image, class type: SaveImage\nPrompt executed in 1.89 seconds\noutputs:  {'9': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nContents of /tmp/outputs:\nComfyUI_00001_.png",
  "metrics": {
    "predict_time": 2.364681,
    "total_time": 2.37292
  },
  "output": [
    "https://replicate.delivery/pbxt/EbAvF2x5pIYDMdjKTMsoUynk9xrw81DlQ9EqLmLHFQ8feovSA/ComfyUI_00001_.webp"
  ],
  "started_at": "2024-04-30T12:01:01.726239Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/em57nhsk2srgp0cf5vgtdjjg4g",
    "cancel": "https://api.replicate.com/v1/predictions/em57nhsk2srgp0cf5vgtdjjg4g/cancel"
  },
  "version": "a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e"
}

Generated in

2.4 seconds

Tweak it ShareReport

Prediction

fofr/ays-text-to-image:a004c3ac

Model

fofr/ays-text-to-image:a004c3ac

ID

50t317j6tsrm80cke9sv9hen68

Status

Succeeded

Source

Web

Hardware

L40S

Total duration

1.3s

Created

4 months ago

Input

steps: 10
width: 1156
height: 768
prompt: a beautiful portrait photo of a cat
checkpoint: ProteusV0.4.safetensors
num_outputs: 1
sampler_name: euler
output_format: webp
guidance_scale: 7.5
output_quality: 80
negative_prompt

{
  "steps": 10,
  "width": 1156,
  "height": 768,
  "prompt": "a beautiful portrait photo of a cat",
  "checkpoint": "ProteusV0.4.safetensors",
  "num_outputs": 1,
  "sampler_name": "euler",
  "output_format": "webp",
  "guidance_scale": 7.5,
  "output_quality": 80,
  "negative_prompt": ""
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run fofr/ays-text-to-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/ays-text-to-image:a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e",
  {
    input: {
      steps: 10,
      width: 1156,
      height: 768,
      prompt: "a beautiful portrait photo of a cat",
      checkpoint: "ProteusV0.4.safetensors",
      num_outputs: 1,
      sampler_name: "euler",
      output_format: "webp",
      guidance_scale: 7.5,
      output_quality: 80,
      negative_prompt: ""
    }
  }
);
console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run fofr/ays-text-to-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/ays-text-to-image:a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e",
    input={
        "steps": 10,
        "width": 1156,
        "height": 768,
        "prompt": "a beautiful portrait photo of a cat",
        "checkpoint": "ProteusV0.4.safetensors",
        "num_outputs": 1,
        "sampler_name": "euler",
        "output_format": "webp",
        "guidance_scale": 7.5,
        "output_quality": 80,
        "negative_prompt": ""
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run fofr/ays-text-to-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e",
    "input": {
      "steps": 10,
      "width": 1156,
      "height": 768,
      "prompt": "a beautiful portrait photo of a cat",
      "checkpoint": "ProteusV0.4.safetensors",
      "num_outputs": 1,
      "sampler_name": "euler",
      "output_format": "webp",
      "guidance_scale": 7.5,
      "output_quality": 80,
      "negative_prompt": ""
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/fofr/ays-text-to-image@sha256:a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e \
  -i 'steps=10' \
  -i 'width=1156' \
  -i 'height=768' \
  -i 'prompt="a beautiful portrait photo of a cat"' \
  -i 'checkpoint="ProteusV0.4.safetensors"' \
  -i 'num_outputs=1' \
  -i 'sampler_name="euler"' \
  -i 'output_format="webp"' \
  -i 'guidance_scale=7.5' \
  -i 'output_quality=80' \
  -i 'negative_prompt=""'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/fofr/ays-text-to-image@sha256:a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "steps": 10,
      "width": 1156,
      "height": 768,
      "prompt": "a beautiful portrait photo of a cat",
      "checkpoint": "ProteusV0.4.safetensors",
      "num_outputs": 1,
      "sampler_name": "euler",
      "output_format": "webp",
      "guidance_scale": 7.5,
      "output_quality": 80,
      "negative_prompt": ""
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

{
  "completed_at": "2024-11-28T11:06:18.936209Z",
  "created_at": "2024-11-28T11:06:17.686000Z",
  "data_removed": false,
  "error": null,
  "id": "50t317j6tsrm80cke9sv9hen68",
  "input": {
    "steps": 10,
    "width": 1156,
    "height": 768,
    "prompt": "a beautiful portrait photo of a cat",
    "checkpoint": "ProteusV0.4.safetensors",
    "num_outputs": 1,
    "sampler_name": "euler",
    "output_format": "webp",
    "guidance_scale": 7.5,
    "output_quality": 80,
    "negative_prompt": ""
  },
  "logs": "Random seed set to: 3470234499\nChecking inputs\n====================================\nChecking weights\n✅ ProteusV0.4.safetensors\n====================================\nRunning workflow\ngot prompt\nExecuting node 21, title: SamplerCustom, class type: SamplerCustom\n  0%|          | 0/10 [00:00<?, ?it/s]\n 20%|██        | 2/10 [00:00<00:00, 16.72it/s]\n 40%|████      | 4/10 [00:00<00:00, 13.17it/s]\n 60%|██████    | 6/10 [00:00<00:00, 12.32it/s]\n 80%|████████  | 8/10 [00:00<00:00, 11.94it/s]\n100%|██████████| 10/10 [00:00<00:00, 11.76it/s]\n100%|██████████| 10/10 [00:00<00:00, 12.21it/s]\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 9, title: Save Image, class type: SaveImage\nPrompt executed in 1.14 seconds\noutputs:  {'9': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nContents of /tmp/outputs:\nComfyUI_00001_.png",
  "metrics": {
    "predict_time": 1.242096476,
    "total_time": 1.250209
  },
  "output": [
    "https://replicate.delivery/xezq/7B9xH1LJjI59N9FtDkG40mHM3sSB3b5MRxwOV7nCbfPVBw6JA/ComfyUI_00001_.webp"
  ],
  "started_at": "2024-11-28T11:06:17.694113Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://stream.replicate.com/v1/files/bcwr-loykbbdz3uq6jpzs7p2mgf6joe6dssl2y3hesyhgle6hgchcubtq",
    "get": "https://api.replicate.com/v1/predictions/50t317j6tsrm80cke9sv9hen68",
    "cancel": "https://api.replicate.com/v1/predictions/50t317j6tsrm80cke9sv9hen68/cancel"
  },
  "version": "a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e"
}

Generated in

1.3 seconds

Tweak it ShareReport

fofr / ays-text-to-image

Prediction

Input

Output

Prediction

Input

Output

Prediction

Input

Output

Prediction

Input

Output

Prediction

Input

Output

Logs (5enrvraw95rgm0cf5veva7rggm)

Logs (v0mctz9t49rgp0cf5vf984jc10)

Logs (n81g2exv6hrgm0cf5vftvh1r38)

Logs (em57nhsk2srgp0cf5vgtdjjg4g)

Logs (50t317j6tsrm80cke9sv9hen68)