ai-forever
/
kandinsky-2.2
multilingual text2image latent diffusion model
Prediction
ai-forever/kandinsky-2.2:ad9d7879ID3tsx2ijbtsa47m4mwbifyiglxmStatusSucceededSourceWebHardwareA100 (40GB)Total durationCreatedby @chenxwhInput
- width
- 1024
- height
- 1024
- prompt
- A moss covered astronaut with a black background
- num_outputs
- 1
- num_inference_steps
- 75
{ "width": 1024, "height": 1024, "prompt": "A moss covered astronaut with a black background", "num_outputs": 1, "num_inference_steps": 75 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run ai-forever/kandinsky-2.2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ai-forever/kandinsky-2.2:ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", { input: { width: 1024, height: 1024, prompt: "A moss covered astronaut with a black background", num_outputs: 1, num_inference_steps: 75 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run ai-forever/kandinsky-2.2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ai-forever/kandinsky-2.2:ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", input={ "width": 1024, "height": 1024, "prompt": "A moss covered astronaut with a black background", "num_outputs": 1, "num_inference_steps": 75 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run ai-forever/kandinsky-2.2 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": "ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", "input": { "width": 1024, "height": 1024, "prompt": "A moss covered astronaut with a black background", "num_outputs": 1, "num_inference_steps": 75 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-07-12T22:23:00.041096Z", "created_at": "2023-07-12T22:22:51.044455Z", "data_removed": false, "error": null, "id": "3tsx2ijbtsa47m4mwbifyiglxm", "input": { "width": 1024, "height": 1024, "prompt": "A moss covered astronaut with a black background", "num_outputs": 1, "num_inference_steps": 75 }, "logs": "Using seed: 4697\n 0%| | 0/25 [00:00<?, ?it/s]\n 20%|██ | 5/25 [00:00<00:00, 40.13it/s]\n 40%|████ | 10/25 [00:00<00:00, 40.19it/s]\n 60%|██████ | 15/25 [00:00<00:00, 40.05it/s]\n 80%|████████ | 20/25 [00:00<00:00, 39.66it/s]\n100%|██████████| 25/25 [00:00<00:00, 39.93it/s]\n100%|██████████| 25/25 [00:00<00:00, 39.90it/s]\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature']\n 0%| | 0/25 [00:00<?, ?it/s]\n 16%|█▌ | 4/25 [00:00<00:00, 37.91it/s]\n 36%|███▌ | 9/25 [00:00<00:00, 39.60it/s]\n 56%|█████▌ | 14/25 [00:00<00:00, 39.87it/s]\n 76%|███████▌ | 19/25 [00:00<00:00, 40.26it/s]\n 96%|█████████▌| 24/25 [00:00<00:00, 40.42it/s]\n100%|██████████| 25/25 [00:00<00:00, 40.12it/s]\n 0%| | 0/75 [00:00<?, ?it/s]\n 1%|▏ | 1/75 [00:00<00:14, 5.06it/s]\n 4%|▍ | 3/75 [00:00<00:08, 8.75it/s]\n 7%|▋ | 5/75 [00:00<00:06, 10.26it/s]\n 9%|▉ | 7/75 [00:00<00:06, 11.00it/s]\n 12%|█▏ | 9/75 [00:00<00:05, 11.45it/s]\n 15%|█▍ | 11/75 [00:01<00:05, 11.72it/s]\n 17%|█▋ | 13/75 [00:01<00:05, 11.89it/s]\n 20%|██ | 15/75 [00:01<00:04, 12.01it/s]\n 23%|██▎ | 17/75 [00:01<00:04, 12.09it/s]\n 25%|██▌ | 19/75 [00:01<00:04, 12.12it/s]\n 28%|██▊ | 21/75 [00:01<00:04, 12.16it/s]\n 31%|███ | 23/75 [00:02<00:04, 12.19it/s]\n 33%|███▎ | 25/75 [00:02<00:04, 12.21it/s]\n 36%|███▌ | 27/75 [00:02<00:03, 12.20it/s]\n 39%|███▊ | 29/75 [00:02<00:03, 12.21it/s]\n 41%|████▏ | 31/75 [00:02<00:03, 12.12it/s]\n 44%|████▍ | 33/75 [00:02<00:03, 12.11it/s]\n 47%|████▋ | 35/75 [00:02<00:03, 12.04it/s]\n 49%|████▉ | 37/75 [00:03<00:03, 11.90it/s]\n 52%|█████▏ | 39/75 [00:03<00:03, 11.98it/s]\n 55%|█████▍ | 41/75 [00:03<00:02, 12.04it/s]\n 57%|█████▋ | 43/75 [00:03<00:02, 12.08it/s]\n 60%|██████ | 45/75 [00:03<00:02, 12.12it/s]\n 63%|██████▎ | 47/75 [00:03<00:02, 12.09it/s]\n 65%|██████▌ | 49/75 [00:04<00:02, 12.06it/s]\n 68%|██████▊ | 51/75 [00:04<00:01, 12.10it/s]\n 71%|███████ | 53/75 [00:04<00:01, 12.14it/s]\n 73%|███████▎ | 55/75 [00:04<00:01, 12.14it/s]\n 76%|███████▌ | 57/75 [00:04<00:01, 12.16it/s]\n 79%|███████▊ | 59/75 [00:04<00:01, 12.18it/s]\n 81%|████████▏ | 61/75 [00:05<00:01, 12.11it/s]\n 84%|████████▍ | 63/75 [00:05<00:00, 12.15it/s]\n 87%|████████▋ | 65/75 [00:05<00:00, 12.14it/s]\n 89%|████████▉ | 67/75 [00:05<00:00, 12.14it/s]\n 92%|█████████▏| 69/75 [00:05<00:00, 12.16it/s]\n 95%|█████████▍| 71/75 [00:05<00:00, 12.19it/s]\n 97%|█████████▋| 73/75 [00:06<00:00, 12.17it/s]\n100%|██████████| 75/75 [00:06<00:00, 12.18it/s]\n100%|██████████| 75/75 [00:06<00:00, 11.92it/s]", "metrics": { "predict_time": 9.029294, "total_time": 8.996641 }, "output": [ "https://replicate.delivery/pbxt/Lca3IEjcKoJBBVS6ajROkK37sDzPsmjYxIcFzxPZp65wZzTE/out-0.png" ], "started_at": "2023-07-12T22:22:51.011802Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/3tsx2ijbtsa47m4mwbifyiglxm", "cancel": "https://api.replicate.com/v1/predictions/3tsx2ijbtsa47m4mwbifyiglxm/cancel" }, "version": "424befb1eae6af8363edb846ae98a11111a39740988baebd279d73fe3ecc92c2" }
Generated inUsing seed: 4697 0%| | 0/25 [00:00<?, ?it/s] 20%|██ | 5/25 [00:00<00:00, 40.13it/s] 40%|████ | 10/25 [00:00<00:00, 40.19it/s] 60%|██████ | 15/25 [00:00<00:00, 40.05it/s] 80%|████████ | 20/25 [00:00<00:00, 39.66it/s] 100%|██████████| 25/25 [00:00<00:00, 39.93it/s] 100%|██████████| 25/25 [00:00<00:00, 39.90it/s] The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature'] 0%| | 0/25 [00:00<?, ?it/s] 16%|█▌ | 4/25 [00:00<00:00, 37.91it/s] 36%|███▌ | 9/25 [00:00<00:00, 39.60it/s] 56%|█████▌ | 14/25 [00:00<00:00, 39.87it/s] 76%|███████▌ | 19/25 [00:00<00:00, 40.26it/s] 96%|█████████▌| 24/25 [00:00<00:00, 40.42it/s] 100%|██████████| 25/25 [00:00<00:00, 40.12it/s] 0%| | 0/75 [00:00<?, ?it/s] 1%|▏ | 1/75 [00:00<00:14, 5.06it/s] 4%|▍ | 3/75 [00:00<00:08, 8.75it/s] 7%|▋ | 5/75 [00:00<00:06, 10.26it/s] 9%|▉ | 7/75 [00:00<00:06, 11.00it/s] 12%|█▏ | 9/75 [00:00<00:05, 11.45it/s] 15%|█▍ | 11/75 [00:01<00:05, 11.72it/s] 17%|█▋ | 13/75 [00:01<00:05, 11.89it/s] 20%|██ | 15/75 [00:01<00:04, 12.01it/s] 23%|██▎ | 17/75 [00:01<00:04, 12.09it/s] 25%|██▌ | 19/75 [00:01<00:04, 12.12it/s] 28%|██▊ | 21/75 [00:01<00:04, 12.16it/s] 31%|███ | 23/75 [00:02<00:04, 12.19it/s] 33%|███▎ | 25/75 [00:02<00:04, 12.21it/s] 36%|███▌ | 27/75 [00:02<00:03, 12.20it/s] 39%|███▊ | 29/75 [00:02<00:03, 12.21it/s] 41%|████▏ | 31/75 [00:02<00:03, 12.12it/s] 44%|████▍ | 33/75 [00:02<00:03, 12.11it/s] 47%|████▋ | 35/75 [00:02<00:03, 12.04it/s] 49%|████▉ | 37/75 [00:03<00:03, 11.90it/s] 52%|█████▏ | 39/75 [00:03<00:03, 11.98it/s] 55%|█████▍ | 41/75 [00:03<00:02, 12.04it/s] 57%|█████▋ | 43/75 [00:03<00:02, 12.08it/s] 60%|██████ | 45/75 [00:03<00:02, 12.12it/s] 63%|██████▎ | 47/75 [00:03<00:02, 12.09it/s] 65%|██████▌ | 49/75 [00:04<00:02, 12.06it/s] 68%|██████▊ | 51/75 [00:04<00:01, 12.10it/s] 71%|███████ | 53/75 [00:04<00:01, 12.14it/s] 73%|███████▎ | 55/75 [00:04<00:01, 12.14it/s] 76%|███████▌ | 57/75 [00:04<00:01, 12.16it/s] 79%|███████▊ | 59/75 [00:04<00:01, 12.18it/s] 81%|████████▏ | 61/75 [00:05<00:01, 12.11it/s] 84%|████████▍ | 63/75 [00:05<00:00, 12.15it/s] 87%|████████▋ | 65/75 [00:05<00:00, 12.14it/s] 89%|████████▉ | 67/75 [00:05<00:00, 12.14it/s] 92%|█████████▏| 69/75 [00:05<00:00, 12.16it/s] 95%|█████████▍| 71/75 [00:05<00:00, 12.19it/s] 97%|█████████▋| 73/75 [00:06<00:00, 12.17it/s] 100%|██████████| 75/75 [00:06<00:00, 12.18it/s] 100%|██████████| 75/75 [00:06<00:00, 11.92it/s]
Prediction
ai-forever/kandinsky-2.2:ad9d7879IDrk7ditbbgtjjq3jmzj3e2znisiStatusSucceededSourceWebHardwareA100 (40GB)Total durationCreatedby @chenxwhInput
- width
- "896"
- height
- 1024
- prompt
- Detailed portrait of a masked woman, bright peacock feathers, complex, elegant, highly detailed, digital painting, art, fluid, illustration, green highlighted lines, complex patterns, cyberpunk Alphonse Mucha
- num_outputs
- 1
- negative_prompt
- num_inference_steps
- 150
{ "width": "896", "height": 1024, "prompt": "Detailed portrait of a masked woman, bright peacock feathers, complex, elegant, highly detailed, digital painting, art, fluid, illustration, green highlighted lines, complex patterns, cyberpunk Alphonse Mucha", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 150 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run ai-forever/kandinsky-2.2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ai-forever/kandinsky-2.2:ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", { input: { width: "896", height: 1024, prompt: "Detailed portrait of a masked woman, bright peacock feathers, complex, elegant, highly detailed, digital painting, art, fluid, illustration, green highlighted lines, complex patterns, cyberpunk Alphonse Mucha", num_outputs: 1, negative_prompt: "", num_inference_steps: 150 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run ai-forever/kandinsky-2.2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ai-forever/kandinsky-2.2:ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", input={ "width": "896", "height": 1024, "prompt": "Detailed portrait of a masked woman, bright peacock feathers, complex, elegant, highly detailed, digital painting, art, fluid, illustration, green highlighted lines, complex patterns, cyberpunk Alphonse Mucha", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 150 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run ai-forever/kandinsky-2.2 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": "ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", "input": { "width": "896", "height": 1024, "prompt": "Detailed portrait of a masked woman, bright peacock feathers, complex, elegant, highly detailed, digital painting, art, fluid, illustration, green highlighted lines, complex patterns, cyberpunk Alphonse Mucha", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 150 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-07-12T22:49:35.539479Z", "created_at": "2023-07-12T22:49:19.523922Z", "data_removed": false, "error": null, "id": "rk7ditbbgtjjq3jmzj3e2znisi", "input": { "width": "896", "height": 1024, "prompt": "Detailed portrait of a masked woman, bright peacock feathers, complex, elegant, highly detailed, digital painting, art, fluid, illustration, green highlighted lines, complex patterns, cyberpunk Alphonse Mucha", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 150 }, "logs": "Using seed: 5244\n 0%| | 0/25 [00:00<?, ?it/s]\n 16%|█▌ | 4/25 [00:00<00:00, 30.67it/s]\n 32%|███▏ | 8/25 [00:00<00:00, 30.49it/s]\n 48%|████▊ | 12/25 [00:00<00:00, 31.12it/s]\n 64%|██████▍ | 16/25 [00:00<00:00, 32.63it/s]\n 80%|████████ | 20/25 [00:00<00:00, 32.16it/s]\n 96%|█████████▌| 24/25 [00:00<00:00, 30.72it/s]\n100%|██████████| 25/25 [00:00<00:00, 30.96it/s]\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature']\n 0%| | 0/25 [00:00<?, ?it/s]\n 16%|█▌ | 4/25 [00:00<00:00, 34.38it/s]\n 32%|███▏ | 8/25 [00:00<00:00, 36.59it/s]\n 48%|████▊ | 12/25 [00:00<00:00, 37.19it/s]\n 64%|██████▍ | 16/25 [00:00<00:00, 37.49it/s]\n 80%|████████ | 20/25 [00:00<00:00, 36.17it/s]\n 96%|█████████▌| 24/25 [00:00<00:00, 36.53it/s]\n100%|██████████| 25/25 [00:00<00:00, 36.19it/s]\n 0%| | 0/150 [00:00<?, ?it/s]\n 1%|▏ | 2/150 [00:00<00:13, 10.82it/s]\n 3%|▎ | 4/150 [00:00<00:12, 11.40it/s]\n 4%|▍ | 6/150 [00:00<00:12, 11.73it/s]\n 5%|▌ | 8/150 [00:00<00:12, 11.75it/s]\n 7%|▋ | 10/150 [00:00<00:11, 11.86it/s]\n 8%|▊ | 12/150 [00:01<00:11, 12.06it/s]\n 9%|▉ | 14/150 [00:01<00:11, 11.98it/s]\n 11%|█ | 16/150 [00:01<00:10, 12.23it/s]\n 12%|█▏ | 18/150 [00:01<00:10, 12.43it/s]\n 13%|█▎ | 20/150 [00:01<00:10, 12.53it/s]\n 15%|█▍ | 22/150 [00:01<00:10, 12.33it/s]\n 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11.60it/s]\n100%|██████████| 150/150 [00:12<00:00, 11.84it/s]\n100%|██████████| 150/150 [00:12<00:00, 11.71it/s]", "metrics": { "predict_time": 16.050058, "total_time": 16.015557 }, "output": [ "https://replicate.delivery/pbxt/2QC5sev3eFg2lUPZrYokF1FYCIGF9YC2BlFtExvMxXKef38EB/out-0.png" ], "started_at": "2023-07-12T22:49:19.489421Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/rk7ditbbgtjjq3jmzj3e2znisi", "cancel": "https://api.replicate.com/v1/predictions/rk7ditbbgtjjq3jmzj3e2znisi/cancel" }, "version": "424befb1eae6af8363edb846ae98a11111a39740988baebd279d73fe3ecc92c2" }
Generated inUsing seed: 5244 0%| | 0/25 [00:00<?, ?it/s] 16%|█▌ | 4/25 [00:00<00:00, 30.67it/s] 32%|███▏ | 8/25 [00:00<00:00, 30.49it/s] 48%|████▊ | 12/25 [00:00<00:00, 31.12it/s] 64%|██████▍ | 16/25 [00:00<00:00, 32.63it/s] 80%|████████ | 20/25 [00:00<00:00, 32.16it/s] 96%|█████████▌| 24/25 [00:00<00:00, 30.72it/s] 100%|██████████| 25/25 [00:00<00:00, 30.96it/s] The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature'] 0%| | 0/25 [00:00<?, ?it/s] 16%|█▌ | 4/25 [00:00<00:00, 34.38it/s] 32%|███▏ | 8/25 [00:00<00:00, 36.59it/s] 48%|████▊ | 12/25 [00:00<00:00, 37.19it/s] 64%|██████▍ | 16/25 [00:00<00:00, 37.49it/s] 80%|████████ | 20/25 [00:00<00:00, 36.17it/s] 96%|█████████▌| 24/25 [00:00<00:00, 36.53it/s] 100%|██████████| 25/25 [00:00<00:00, 36.19it/s] 0%| | 0/150 [00:00<?, ?it/s] 1%|▏ | 2/150 [00:00<00:13, 10.82it/s] 3%|▎ | 4/150 [00:00<00:12, 11.40it/s] 4%|▍ | 6/150 [00:00<00:12, 11.73it/s] 5%|▌ | 8/150 [00:00<00:12, 11.75it/s] 7%|▋ | 10/150 [00:00<00:11, 11.86it/s] 8%|▊ | 12/150 [00:01<00:11, 12.06it/s] 9%|▉ | 14/150 [00:01<00:11, 11.98it/s] 11%|█ | 16/150 [00:01<00:10, 12.23it/s] 12%|█▏ | 18/150 [00:01<00:10, 12.43it/s] 13%|█▎ | 20/150 [00:01<00:10, 12.53it/s] 15%|█▍ | 22/150 [00:01<00:10, 12.33it/s] 16%|█▌ | 24/150 [00:01<00:10, 12.15it/s] 17%|█▋ | 26/150 [00:02<00:10, 12.13it/s] 19%|█▊ | 28/150 [00:02<00:10, 12.12it/s] 20%|██ | 30/150 [00:02<00:09, 12.35it/s] 21%|██▏ | 32/150 [00:02<00:09, 12.29it/s] 23%|██▎ | 34/150 [00:02<00:09, 11.97it/s] 24%|██▍ | 36/150 [00:02<00:09, 11.76it/s] 25%|██▌ | 38/150 [00:03<00:09, 11.56it/s] 27%|██▋ | 40/150 [00:03<00:09, 11.49it/s] 28%|██▊ | 42/150 [00:03<00:09, 11.91it/s] 29%|██▉ | 44/150 [00:03<00:08, 11.85it/s] 31%|███ | 46/150 [00:03<00:08, 11.90it/s] 32%|███▏ | 48/150 [00:04<00:08, 12.08it/s] 33%|███▎ | 50/150 [00:04<00:08, 12.11it/s] 35%|███▍ | 52/150 [00:04<00:08, 12.10it/s] 36%|███▌ | 54/150 [00:04<00:08, 11.94it/s] 37%|███▋ | 56/150 [00:04<00:07, 12.03it/s] 39%|███▊ | 58/150 [00:04<00:07, 12.19it/s] 40%|████ | 60/150 [00:04<00:07, 12.00it/s] 41%|████▏ | 62/150 [00:05<00:07, 11.91it/s] 43%|████▎ | 64/150 [00:05<00:07, 11.79it/s] 44%|████▍ | 66/150 [00:05<00:07, 11.58it/s] 45%|████▌ | 68/150 [00:05<00:07, 11.63it/s] 47%|████▋ | 70/150 [00:05<00:06, 11.60it/s] 48%|████▊ | 72/150 [00:06<00:06, 11.75it/s] 49%|████▉ | 74/150 [00:06<00:06, 11.62it/s] 51%|█████ | 76/150 [00:06<00:06, 11.64it/s] 52%|█████▏ | 78/150 [00:06<00:06, 11.69it/s] 53%|█████▎ | 80/150 [00:06<00:06, 11.59it/s] 55%|█████▍ | 82/150 [00:06<00:05, 11.40it/s] 56%|█████▌ | 84/150 [00:07<00:05, 11.53it/s] 57%|█████▋ | 86/150 [00:07<00:05, 11.80it/s] 59%|█████▊ | 88/150 [00:07<00:05, 11.69it/s] 60%|██████ | 90/150 [00:07<00:05, 11.61it/s] 61%|██████▏ | 92/150 [00:07<00:05, 11.39it/s] 63%|██████▎ | 94/150 [00:07<00:04, 11.48it/s] 64%|██████▍ | 96/150 [00:08<00:04, 11.36it/s] 65%|██████▌ | 98/150 [00:08<00:04, 11.20it/s] 67%|██████▋ | 100/150 [00:08<00:04, 11.35it/s] 68%|██████▊ | 102/150 [00:08<00:04, 11.26it/s] 69%|██████▉ | 104/150 [00:08<00:04, 11.11it/s] 71%|███████ | 106/150 [00:09<00:03, 11.22it/s] 72%|███████▏ | 108/150 [00:09<00:03, 11.20it/s] 73%|███████▎ | 110/150 [00:09<00:03, 11.22it/s] 75%|███████▍ | 112/150 [00:09<00:03, 11.27it/s] 76%|███████▌ | 114/150 [00:09<00:03, 11.24it/s] 77%|███████▋ | 116/150 [00:09<00:03, 11.31it/s] 79%|███████▊ | 118/150 [00:10<00:02, 11.73it/s] 80%|████████ | 120/150 [00:10<00:02, 11.98it/s] 81%|████████▏ | 122/150 [00:10<00:02, 11.74it/s] 83%|████████▎ | 124/150 [00:10<00:02, 11.91it/s] 84%|████████▍ | 126/150 [00:10<00:02, 11.88it/s] 85%|████████▌ | 128/150 [00:10<00:01, 11.67it/s] 87%|████████▋ | 130/150 [00:11<00:01, 11.73it/s] 88%|████████▊ | 132/150 [00:11<00:01, 11.62it/s] 89%|████████▉ | 134/150 [00:11<00:01, 11.44it/s] 91%|█████████ | 136/150 [00:11<00:01, 11.44it/s] 92%|█████████▏| 138/150 [00:11<00:01, 11.33it/s] 93%|█████████▎| 140/150 [00:11<00:00, 11.39it/s] 95%|█████████▍| 142/150 [00:12<00:00, 11.44it/s] 96%|█████████▌| 144/150 [00:12<00:00, 11.32it/s] 97%|█████████▋| 146/150 [00:12<00:00, 11.29it/s] 99%|█████████▊| 148/150 [00:12<00:00, 11.60it/s] 100%|██████████| 150/150 [00:12<00:00, 11.84it/s] 100%|██████████| 150/150 [00:12<00:00, 11.71it/s]
Prediction
ai-forever/kandinsky-2.2:ad9d7879IDkqs3jtrblkmqj63ji5ys6wmxyeStatusSucceededSourceWebHardwareA100 (40GB)Total durationCreatedby @chenxwhInput
- width
- "1024"
- height
- 1024
- prompt
- a beautiful landscape photo, epic, dawn light, 8k, mountains, river, dramatic, award winning
- num_outputs
- 1
- negative_prompt
- num_inference_steps
- 150
{ "width": "1024", "height": 1024, "prompt": "a beautiful landscape photo, epic, dawn light, 8k, mountains, river, dramatic, award winning", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 150 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run ai-forever/kandinsky-2.2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ai-forever/kandinsky-2.2:ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", { input: { width: "1024", height: 1024, prompt: "a beautiful landscape photo, epic, dawn light, 8k, mountains, river, dramatic, award winning", num_outputs: 1, negative_prompt: "", num_inference_steps: 150 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run ai-forever/kandinsky-2.2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ai-forever/kandinsky-2.2:ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", input={ "width": "1024", "height": 1024, "prompt": "a beautiful landscape photo, epic, dawn light, 8k, mountains, river, dramatic, award winning", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 150 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run ai-forever/kandinsky-2.2 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": "ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", "input": { "width": "1024", "height": 1024, "prompt": "a beautiful landscape photo, epic, dawn light, 8k, mountains, river, dramatic, award winning", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 150 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-07-12T22:50:17.997978Z", "created_at": "2023-07-12T22:50:00.957701Z", "data_removed": false, "error": null, "id": "kqs3jtrblkmqj63ji5ys6wmxye", "input": { "width": "1024", "height": 1024, "prompt": "a beautiful landscape photo, epic, dawn light, 8k, mountains, river, dramatic, award winning", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 150 }, "logs": "Using seed: 3685\n 0%| | 0/25 [00:00<?, ?it/s]\n 16%|█▌ | 4/25 [00:00<00:00, 33.33it/s]\n 32%|███▏ | 8/25 [00:00<00:00, 35.77it/s]\n 48%|████▊ | 12/25 [00:00<00:00, 34.67it/s]\n 64%|██████▍ | 16/25 [00:00<00:00, 34.89it/s]\n 80%|████████ | 20/25 [00:00<00:00, 34.08it/s]\n 96%|█████████▌| 24/25 [00:00<00:00, 32.91it/s]\n100%|██████████| 25/25 [00:00<00:00, 33.59it/s]\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature']\n 0%| | 0/25 [00:00<?, ?it/s]\n 16%|█▌ | 4/25 [00:00<00:00, 30.70it/s]\n 32%|███▏ | 8/25 [00:00<00:00, 30.76it/s]\n 48%|████▊ | 12/25 [00:00<00:00, 32.05it/s]\n 64%|██████▍ | 16/25 [00:00<00:00, 32.34it/s]\n 80%|████████ | 20/25 [00:00<00:00, 32.73it/s]\n 96%|█████████▌| 24/25 [00:00<00:00, 32.28it/s]\n100%|██████████| 25/25 [00:00<00:00, 32.08it/s]\n 0%| | 0/150 [00:00<?, ?it/s]\n 1%| | 1/150 [00:00<00:15, 9.84it/s]\n 1%|▏ | 2/150 [00:00<00:14, 9.91it/s]\n 3%|▎ | 4/150 [00:00<00:14, 10.41it/s]\n 4%|▍ | 6/150 [00:00<00:13, 10.59it/s]\n 5%|▌ | 8/150 [00:00<00:13, 10.79it/s]\n 7%|▋ | 10/150 [00:00<00:12, 11.20it/s]\n 8%|▊ | 12/150 [00:01<00:12, 11.13it/s]\n 9%|▉ | 14/150 [00:01<00:12, 11.11it/s]\n 11%|█ | 16/150 [00:01<00:12, 11.05it/s]\n 12%|█▏ | 18/150 [00:01<00:11, 11.06it/s]\n 13%|█▎ | 20/150 [00:01<00:11, 10.94it/s]\n 15%|█▍ | 22/150 [00:02<00:11, 11.15it/s]\n 16%|█▌ | 24/150 [00:02<00:11, 11.33it/s]\n 17%|█▋ | 26/150 [00:02<00:11, 11.18it/s]\n 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[00:13<00:00, 10.98it/s]", "metrics": { "predict_time": 17.07321, "total_time": 17.040277 }, "output": [ "https://replicate.delivery/pbxt/79ESGrLVzgZyCdfQ4a4o5kJeJbfIOTXTaeuiUItYbEcmC48EB/out-0.png" ], "started_at": "2023-07-12T22:50:00.924768Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/kqs3jtrblkmqj63ji5ys6wmxye", "cancel": "https://api.replicate.com/v1/predictions/kqs3jtrblkmqj63ji5ys6wmxye/cancel" }, "version": "424befb1eae6af8363edb846ae98a11111a39740988baebd279d73fe3ecc92c2" }
Generated inUsing seed: 3685 0%| | 0/25 [00:00<?, ?it/s] 16%|█▌ | 4/25 [00:00<00:00, 33.33it/s] 32%|███▏ | 8/25 [00:00<00:00, 35.77it/s] 48%|████▊ | 12/25 [00:00<00:00, 34.67it/s] 64%|██████▍ | 16/25 [00:00<00:00, 34.89it/s] 80%|████████ | 20/25 [00:00<00:00, 34.08it/s] 96%|█████████▌| 24/25 [00:00<00:00, 32.91it/s] 100%|██████████| 25/25 [00:00<00:00, 33.59it/s] The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature'] 0%| | 0/25 [00:00<?, ?it/s] 16%|█▌ | 4/25 [00:00<00:00, 30.70it/s] 32%|███▏ | 8/25 [00:00<00:00, 30.76it/s] 48%|████▊ | 12/25 [00:00<00:00, 32.05it/s] 64%|██████▍ | 16/25 [00:00<00:00, 32.34it/s] 80%|████████ | 20/25 [00:00<00:00, 32.73it/s] 96%|█████████▌| 24/25 [00:00<00:00, 32.28it/s] 100%|██████████| 25/25 [00:00<00:00, 32.08it/s] 0%| | 0/150 [00:00<?, ?it/s] 1%| | 1/150 [00:00<00:15, 9.84it/s] 1%|▏ | 2/150 [00:00<00:14, 9.91it/s] 3%|▎ | 4/150 [00:00<00:14, 10.41it/s] 4%|▍ | 6/150 [00:00<00:13, 10.59it/s] 5%|▌ | 8/150 [00:00<00:13, 10.79it/s] 7%|▋ | 10/150 [00:00<00:12, 11.20it/s] 8%|▊ | 12/150 [00:01<00:12, 11.13it/s] 9%|▉ | 14/150 [00:01<00:12, 11.11it/s] 11%|█ | 16/150 [00:01<00:12, 11.05it/s] 12%|█▏ | 18/150 [00:01<00:11, 11.06it/s] 13%|█▎ | 20/150 [00:01<00:11, 10.94it/s] 15%|█▍ | 22/150 [00:02<00:11, 11.15it/s] 16%|█▌ | 24/150 [00:02<00:11, 11.33it/s] 17%|█▋ | 26/150 [00:02<00:11, 11.18it/s] 19%|█▊ | 28/150 [00:02<00:11, 11.05it/s] 20%|██ | 30/150 [00:02<00:10, 10.93it/s] 21%|██▏ | 32/150 [00:02<00:10, 11.00it/s] 23%|██▎ | 34/150 [00:03<00:10, 10.97it/s] 24%|██▍ | 36/150 [00:03<00:10, 10.86it/s] 25%|██▌ | 38/150 [00:03<00:10, 10.68it/s] 27%|██▋ | 40/150 [00:03<00:10, 10.81it/s] 28%|██▊ | 42/150 [00:03<00:09, 10.97it/s] 29%|██▉ | 44/150 [00:04<00:09, 10.92it/s] 31%|███ | 46/150 [00:04<00:09, 10.95it/s] 32%|███▏ | 48/150 [00:04<00:09, 11.08it/s] 33%|███▎ | 50/150 [00:04<00:09, 10.94it/s] 35%|███▍ | 52/150 [00:04<00:08, 10.91it/s] 36%|███▌ | 54/150 [00:04<00:08, 10.87it/s] 37%|███▋ | 56/150 [00:05<00:08, 10.86it/s] 39%|███▊ | 58/150 [00:05<00:08, 11.07it/s] 40%|████ | 60/150 [00:05<00:08, 11.09it/s] 41%|████▏ | 62/150 [00:05<00:07, 11.08it/s] 43%|████▎ | 64/150 [00:05<00:07, 10.98it/s] 44%|████▍ | 66/150 [00:06<00:07, 11.11it/s] 45%|████▌ | 68/150 [00:06<00:07, 11.23it/s] 47%|████▋ | 70/150 [00:06<00:07, 11.27it/s] 48%|████▊ | 72/150 [00:06<00:06, 11.17it/s] 49%|████▉ | 74/150 [00:06<00:06, 11.03it/s] 51%|█████ | 76/150 [00:06<00:06, 11.17it/s] 52%|█████▏ | 78/150 [00:07<00:06, 11.12it/s] 53%|█████▎ | 80/150 [00:07<00:06, 11.24it/s] 55%|█████▍ | 82/150 [00:07<00:06, 11.17it/s] 56%|█████▌ | 84/150 [00:07<00:05, 11.13it/s] 57%|█████▋ | 86/150 [00:07<00:05, 11.16it/s] 59%|█████▊ | 88/150 [00:07<00:05, 11.26it/s] 60%|██████ | 90/150 [00:08<00:05, 11.48it/s] 61%|██████▏ | 92/150 [00:08<00:05, 11.08it/s] 63%|██████▎ | 94/150 [00:08<00:05, 10.90it/s] 64%|██████▍ | 96/150 [00:08<00:04, 11.22it/s] 65%|██████▌ | 98/150 [00:08<00:04, 11.31it/s] 67%|██████▋ | 100/150 [00:09<00:04, 11.21it/s] 68%|██████▊ | 102/150 [00:09<00:04, 11.09it/s] 69%|██████▉ | 104/150 [00:09<00:04, 10.92it/s] 71%|███████ | 106/150 [00:09<00:04, 10.84it/s] 72%|███████▏ | 108/150 [00:09<00:03, 10.75it/s] 73%|███████▎ | 110/150 [00:09<00:03, 10.94it/s] 75%|███████▍ | 112/150 [00:10<00:03, 11.07it/s] 76%|███████▌ | 114/150 [00:10<00:03, 10.93it/s] 77%|███████▋ | 116/150 [00:10<00:03, 11.12it/s] 79%|███████▊ | 118/150 [00:10<00:02, 10.93it/s] 80%|████████ | 120/150 [00:10<00:02, 10.77it/s] 81%|████████▏ | 122/150 [00:11<00:02, 10.76it/s] 83%|████████▎ | 124/150 [00:11<00:02, 10.75it/s] 84%|████████▍ | 126/150 [00:11<00:02, 10.61it/s] 85%|████████▌ | 128/150 [00:11<00:02, 10.54it/s] 87%|████████▋ | 130/150 [00:11<00:01, 10.77it/s] 88%|████████▊ | 132/150 [00:12<00:01, 10.91it/s] 89%|████████▉ | 134/150 [00:12<00:01, 10.87it/s] 91%|█████████ | 136/150 [00:12<00:01, 11.00it/s] 92%|█████████▏| 138/150 [00:12<00:01, 10.82it/s] 93%|█████████▎| 140/150 [00:12<00:00, 10.59it/s] 95%|█████████▍| 142/150 [00:12<00:00, 10.84it/s] 96%|█████████▌| 144/150 [00:13<00:00, 10.90it/s] 97%|█████████▋| 146/150 [00:13<00:00, 10.97it/s] 99%|█████████▊| 148/150 [00:13<00:00, 10.92it/s] 100%|██████████| 150/150 [00:13<00:00, 11.09it/s] 100%|██████████| 150/150 [00:13<00:00, 10.98it/s]
Prediction
ai-forever/kandinsky-2.2:ad9d7879IDwdlrrfrbhu2kfpexi2kbszcgtiStatusSucceededSourceWebHardwareA100 (40GB)Total durationCreatedby @chenxwhInput
- width
- "1024"
- height
- 1024
- prompt
- HD quality, futuristic future cityscape, unusual apartment buildings, architecture, light, dawn, details, Milky Way, 8k
- num_outputs
- 1
- negative_prompt
- num_inference_steps
- 100
{ "width": "1024", "height": 1024, "prompt": "HD quality, futuristic future cityscape, unusual apartment buildings, architecture, light, dawn, details, Milky Way, 8k", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 100 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run ai-forever/kandinsky-2.2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ai-forever/kandinsky-2.2:ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", { input: { width: "1024", height: 1024, prompt: "HD quality, futuristic future cityscape, unusual apartment buildings, architecture, light, dawn, details, Milky Way, 8k", num_outputs: 1, negative_prompt: "", num_inference_steps: 100 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run ai-forever/kandinsky-2.2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ai-forever/kandinsky-2.2:ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", input={ "width": "1024", "height": 1024, "prompt": "HD quality, futuristic future cityscape, unusual apartment buildings, architecture, light, dawn, details, Milky Way, 8k", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 100 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run ai-forever/kandinsky-2.2 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": "ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", "input": { "width": "1024", "height": 1024, "prompt": "HD quality, futuristic future cityscape, unusual apartment buildings, architecture, light, dawn, details, Milky Way, 8k", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 100 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-07-12T22:56:18.632944Z", "created_at": "2023-07-12T22:56:07.468519Z", "data_removed": false, "error": null, "id": "wdlrrfrbhu2kfpexi2kbszcgti", "input": { "width": "1024", "height": 1024, "prompt": "HD quality, futuristic future cityscape, unusual apartment buildings, architecture, light, dawn, details, Milky Way, 8k", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 100 }, "logs": "Using seed: 51138\n 0%| | 0/25 [00:00<?, ?it/s]\n 20%|██ | 5/25 [00:00<00:00, 40.77it/s]\n 40%|████ | 10/25 [00:00<00:00, 40.52it/s]\n 60%|██████ | 15/25 [00:00<00:00, 41.19it/s]\n 80%|████████ | 20/25 [00:00<00:00, 40.79it/s]\n100%|██████████| 25/25 [00:00<00:00, 40.31it/s]\n100%|██████████| 25/25 [00:00<00:00, 40.51it/s]\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature']\n 0%| | 0/25 [00:00<?, ?it/s]\n 20%|██ | 5/25 [00:00<00:00, 41.57it/s]\n 40%|████ | 10/25 [00:00<00:00, 41.63it/s]\n 60%|██████ | 15/25 [00:00<00:00, 40.67it/s]\n 80%|████████ | 20/25 [00:00<00:00, 40.62it/s]\n100%|██████████| 25/25 [00:00<00:00, 40.89it/s]\n100%|██████████| 25/25 [00:00<00:00, 40.91it/s]\n 0%| | 0/100 [00:00<?, ?it/s]\n 1%| | 1/100 [00:00<00:09, 9.90it/s]\n 2%|▏ | 2/100 [00:00<00:09, 9.86it/s]\n 4%|▍ | 4/100 [00:00<00:08, 11.08it/s]\n 6%|▌ | 6/100 [00:00<00:08, 11.57it/s]\n 8%|▊ | 8/100 [00:00<00:07, 11.82it/s]\n 10%|█ | 10/100 [00:00<00:07, 11.97it/s]\n 12%|█▏ | 12/100 [00:01<00:07, 12.06it/s]\n 14%|█▍ | 14/100 [00:01<00:07, 12.09it/s]\n 16%|█▌ | 16/100 [00:01<00:06, 12.06it/s]\n 18%|█▊ | 18/100 [00:01<00:06, 12.11it/s]\n 20%|██ | 20/100 [00:01<00:06, 12.08it/s]\n 22%|██▏ | 22/100 [00:01<00:06, 12.07it/s]\n 24%|██▍ | 24/100 [00:02<00:06, 12.12it/s]\n 26%|██▌ | 26/100 [00:02<00:06, 12.16it/s]\n 28%|██▊ | 28/100 [00:02<00:05, 12.17it/s]\n 30%|███ | 30/100 [00:02<00:05, 12.20it/s]\n 32%|███▏ | 32/100 [00:02<00:05, 12.22it/s]\n 34%|███▍ | 34/100 [00:02<00:05, 12.21it/s]\n 36%|███▌ | 36/100 [00:02<00:05, 12.22it/s]\n 38%|███▊ | 38/100 [00:03<00:05, 12.23it/s]\n 40%|████ | 40/100 [00:03<00:04, 12.17it/s]\n 42%|████▏ | 42/100 [00:03<00:04, 12.13it/s]\n 44%|████▍ | 44/100 [00:03<00:04, 12.15it/s]\n 46%|████▌ | 46/100 [00:03<00:04, 12.18it/s]\n 48%|████▊ | 48/100 [00:03<00:04, 12.18it/s]\n 50%|█████ | 50/100 [00:04<00:04, 12.17it/s]\n 52%|█████▏ | 52/100 [00:04<00:03, 12.08it/s]\n 54%|█████▍ | 54/100 [00:04<00:03, 12.10it/s]\n 56%|█████▌ | 56/100 [00:04<00:03, 12.15it/s]\n 58%|█████▊ | 58/100 [00:04<00:03, 12.12it/s]\n 60%|██████ | 60/100 [00:04<00:03, 12.16it/s]\n 62%|██████▏ | 62/100 [00:05<00:03, 12.18it/s]\n 64%|██████▍ | 64/100 [00:05<00:02, 12.18it/s]\n 66%|██████▌ | 66/100 [00:05<00:02, 12.15it/s]\n 68%|██████▊ | 68/100 [00:05<00:02, 12.18it/s]\n 70%|███████ | 70/100 [00:05<00:02, 12.20it/s]\n 72%|███████▏ | 72/100 [00:05<00:02, 12.20it/s]\n 74%|███████▍ | 74/100 [00:06<00:02, 12.22it/s]\n 76%|███████▌ | 76/100 [00:06<00:01, 12.20it/s]\n 78%|███████▊ | 78/100 [00:06<00:01, 12.16it/s]\n 80%|████████ | 80/100 [00:06<00:01, 12.18it/s]\n 82%|████████▏ | 82/100 [00:06<00:01, 12.19it/s]\n 84%|████████▍ | 84/100 [00:06<00:01, 12.21it/s]\n 86%|████████▌ | 86/100 [00:07<00:01, 12.22it/s]\n 88%|████████▊ | 88/100 [00:07<00:00, 12.19it/s]\n 90%|█████████ | 90/100 [00:07<00:00, 12.20it/s]\n 92%|█████████▏| 92/100 [00:07<00:00, 12.21it/s]\n 94%|█████████▍| 94/100 [00:07<00:00, 12.21it/s]\n 96%|█████████▌| 96/100 [00:07<00:00, 12.22it/s]\n 98%|█████████▊| 98/100 [00:08<00:00, 12.23it/s]\n100%|██████████| 100/100 [00:08<00:00, 12.22it/s]\n100%|██████████| 100/100 [00:08<00:00, 12.12it/s]", "metrics": { "predict_time": 11.200704, "total_time": 11.164425 }, "output": [ "https://replicate.delivery/pbxt/h1FRZp5d5gZfHyyKTA8vJfjAVXbMv4BI5GkkVfVkp1HjMceEB/out-0.png" ], "started_at": "2023-07-12T22:56:07.432240Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/wdlrrfrbhu2kfpexi2kbszcgti", "cancel": "https://api.replicate.com/v1/predictions/wdlrrfrbhu2kfpexi2kbszcgti/cancel" }, "version": "424befb1eae6af8363edb846ae98a11111a39740988baebd279d73fe3ecc92c2" }
Generated inUsing seed: 51138 0%| | 0/25 [00:00<?, ?it/s] 20%|██ | 5/25 [00:00<00:00, 40.77it/s] 40%|████ | 10/25 [00:00<00:00, 40.52it/s] 60%|██████ | 15/25 [00:00<00:00, 41.19it/s] 80%|████████ | 20/25 [00:00<00:00, 40.79it/s] 100%|██████████| 25/25 [00:00<00:00, 40.31it/s] 100%|██████████| 25/25 [00:00<00:00, 40.51it/s] The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature'] 0%| | 0/25 [00:00<?, ?it/s] 20%|██ | 5/25 [00:00<00:00, 41.57it/s] 40%|████ | 10/25 [00:00<00:00, 41.63it/s] 60%|██████ | 15/25 [00:00<00:00, 40.67it/s] 80%|████████ | 20/25 [00:00<00:00, 40.62it/s] 100%|██████████| 25/25 [00:00<00:00, 40.89it/s] 100%|██████████| 25/25 [00:00<00:00, 40.91it/s] 0%| | 0/100 [00:00<?, ?it/s] 1%| | 1/100 [00:00<00:09, 9.90it/s] 2%|▏ | 2/100 [00:00<00:09, 9.86it/s] 4%|▍ | 4/100 [00:00<00:08, 11.08it/s] 6%|▌ | 6/100 [00:00<00:08, 11.57it/s] 8%|▊ | 8/100 [00:00<00:07, 11.82it/s] 10%|█ | 10/100 [00:00<00:07, 11.97it/s] 12%|█▏ | 12/100 [00:01<00:07, 12.06it/s] 14%|█▍ | 14/100 [00:01<00:07, 12.09it/s] 16%|█▌ | 16/100 [00:01<00:06, 12.06it/s] 18%|█▊ | 18/100 [00:01<00:06, 12.11it/s] 20%|██ | 20/100 [00:01<00:06, 12.08it/s] 22%|██▏ | 22/100 [00:01<00:06, 12.07it/s] 24%|██▍ | 24/100 [00:02<00:06, 12.12it/s] 26%|██▌ | 26/100 [00:02<00:06, 12.16it/s] 28%|██▊ | 28/100 [00:02<00:05, 12.17it/s] 30%|███ | 30/100 [00:02<00:05, 12.20it/s] 32%|███▏ | 32/100 [00:02<00:05, 12.22it/s] 34%|███▍ | 34/100 [00:02<00:05, 12.21it/s] 36%|███▌ | 36/100 [00:02<00:05, 12.22it/s] 38%|███▊ | 38/100 [00:03<00:05, 12.23it/s] 40%|████ | 40/100 [00:03<00:04, 12.17it/s] 42%|████▏ | 42/100 [00:03<00:04, 12.13it/s] 44%|████▍ | 44/100 [00:03<00:04, 12.15it/s] 46%|████▌ | 46/100 [00:03<00:04, 12.18it/s] 48%|████▊ | 48/100 [00:03<00:04, 12.18it/s] 50%|█████ | 50/100 [00:04<00:04, 12.17it/s] 52%|█████▏ | 52/100 [00:04<00:03, 12.08it/s] 54%|█████▍ | 54/100 [00:04<00:03, 12.10it/s] 56%|█████▌ | 56/100 [00:04<00:03, 12.15it/s] 58%|█████▊ | 58/100 [00:04<00:03, 12.12it/s] 60%|██████ | 60/100 [00:04<00:03, 12.16it/s] 62%|██████▏ | 62/100 [00:05<00:03, 12.18it/s] 64%|██████▍ | 64/100 [00:05<00:02, 12.18it/s] 66%|██████▌ | 66/100 [00:05<00:02, 12.15it/s] 68%|██████▊ | 68/100 [00:05<00:02, 12.18it/s] 70%|███████ | 70/100 [00:05<00:02, 12.20it/s] 72%|███████▏ | 72/100 [00:05<00:02, 12.20it/s] 74%|███████▍ | 74/100 [00:06<00:02, 12.22it/s] 76%|███████▌ | 76/100 [00:06<00:01, 12.20it/s] 78%|███████▊ | 78/100 [00:06<00:01, 12.16it/s] 80%|████████ | 80/100 [00:06<00:01, 12.18it/s] 82%|████████▏ | 82/100 [00:06<00:01, 12.19it/s] 84%|████████▍ | 84/100 [00:06<00:01, 12.21it/s] 86%|████████▌ | 86/100 [00:07<00:01, 12.22it/s] 88%|████████▊ | 88/100 [00:07<00:00, 12.19it/s] 90%|█████████ | 90/100 [00:07<00:00, 12.20it/s] 92%|█████████▏| 92/100 [00:07<00:00, 12.21it/s] 94%|█████████▍| 94/100 [00:07<00:00, 12.21it/s] 96%|█████████▌| 96/100 [00:07<00:00, 12.22it/s] 98%|█████████▊| 98/100 [00:08<00:00, 12.23it/s] 100%|██████████| 100/100 [00:08<00:00, 12.22it/s] 100%|██████████| 100/100 [00:08<00:00, 12.12it/s]
Prediction
ai-forever/kandinsky-2.2:ad9d7879IDlokruybbg3jnq3wf6d6v276qa4StatusSucceededSourceWebHardwareA100 (40GB)Total durationCreatedby @chenxwhInput
- width
- "1024"
- height
- 1024
- prompt
- a red cat photo, 8k
- num_outputs
- 1
- negative_prompt
- num_inference_steps
- 100
{ "width": "1024", "height": 1024, "prompt": "a red cat photo, 8k", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 100 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run ai-forever/kandinsky-2.2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ai-forever/kandinsky-2.2:ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", { input: { width: "1024", height: 1024, prompt: "a red cat photo, 8k", num_outputs: 1, negative_prompt: "", num_inference_steps: 100 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run ai-forever/kandinsky-2.2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ai-forever/kandinsky-2.2:ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", input={ "width": "1024", "height": 1024, "prompt": "a red cat photo, 8k", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 100 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run ai-forever/kandinsky-2.2 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": "ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", "input": { "width": "1024", "height": 1024, "prompt": "a red cat photo, 8k", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 100 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-07-12T22:57:07.348313Z", "created_at": "2023-07-12T22:56:54.848291Z", "data_removed": false, "error": null, "id": "lokruybbg3jnq3wf6d6v276qa4", "input": { "width": "1024", "height": 1024, "prompt": "a red cat photo, 8k", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 100 }, "logs": "Using seed: 50269\n 0%| | 0/25 [00:00<?, ?it/s]\n 12%|█▏ | 3/25 [00:00<00:00, 28.90it/s]\n 24%|██▍ | 6/25 [00:00<00:00, 28.75it/s]\n 36%|███▌ | 9/25 [00:00<00:00, 28.94it/s]\n 52%|█████▏ | 13/25 [00:00<00:00, 30.29it/s]\n 68%|██████▊ | 17/25 [00:00<00:00, 32.88it/s]\n 84%|████████▍ | 21/25 [00:00<00:00, 33.36it/s]\n100%|██████████| 25/25 [00:00<00:00, 30.96it/s]\n100%|██████████| 25/25 [00:00<00:00, 30.98it/s]\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature']\n 0%| | 0/25 [00:00<?, ?it/s]\n 16%|█▌ | 4/25 [00:00<00:00, 37.45it/s]\n 32%|███▏ | 8/25 [00:00<00:00, 36.14it/s]\n 48%|████▊ | 12/25 [00:00<00:00, 33.41it/s]\n 64%|██████▍ | 16/25 [00:00<00:00, 32.57it/s]\n 80%|████████ | 20/25 [00:00<00:00, 30.45it/s]\n 96%|█████████▌| 24/25 [00:00<00:00, 30.95it/s]\n100%|██████████| 25/25 [00:00<00:00, 31.65it/s]\n 0%| | 0/100 [00:00<?, ?it/s]\n 2%|▏ | 2/100 [00:00<00:09, 10.35it/s]\n 4%|▍ | 4/100 [00:00<00:08, 10.68it/s]\n 6%|▌ | 6/100 [00:00<00:08, 10.72it/s]\n 8%|▊ | 8/100 [00:00<00:08, 10.72it/s]\n 10%|█ | 10/100 [00:00<00:08, 10.80it/s]\n 12%|█▏ | 12/100 [00:01<00:08, 10.81it/s]\n 14%|█▍ | 14/100 [00:01<00:07, 10.86it/s]\n 16%|█▌ | 16/100 [00:01<00:07, 10.87it/s]\n 18%|█▊ | 18/100 [00:01<00:07, 10.85it/s]\n 20%|██ | 20/100 [00:01<00:07, 10.92it/s]\n 22%|██▏ | 22/100 [00:02<00:07, 10.83it/s]\n 24%|██▍ | 24/100 [00:02<00:07, 10.69it/s]\n 26%|██▌ | 26/100 [00:02<00:06, 10.60it/s]\n 28%|██▊ | 28/100 [00:02<00:06, 10.63it/s]\n 30%|███ | 30/100 [00:02<00:06, 10.79it/s]\n 32%|███▏ | 32/100 [00:02<00:06, 10.83it/s]\n 34%|███▍ | 34/100 [00:03<00:06, 10.69it/s]\n 36%|███▌ | 36/100 [00:03<00:06, 10.58it/s]\n 38%|███▊ | 38/100 [00:03<00:05, 10.46it/s]\n 40%|████ | 40/100 [00:03<00:05, 10.43it/s]\n 42%|████▏ | 42/100 [00:03<00:05, 10.67it/s]\n 44%|████▍ | 44/100 [00:04<00:05, 10.95it/s]\n 46%|████▌ | 46/100 [00:04<00:04, 11.05it/s]\n 48%|████▊ | 48/100 [00:04<00:04, 11.14it/s]\n 50%|█████ | 50/100 [00:04<00:04, 11.08it/s]\n 52%|█████▏ | 52/100 [00:04<00:04, 11.09it/s]\n 54%|█████▍ | 54/100 [00:04<00:04, 11.09it/s]\n 56%|█████▌ | 56/100 [00:05<00:03, 11.14it/s]\n 58%|█████▊ | 58/100 [00:05<00:03, 11.06it/s]\n 60%|██████ | 60/100 [00:05<00:03, 10.93it/s]\n 62%|██████▏ | 62/100 [00:05<00:03, 10.97it/s]\n 64%|██████▍ | 64/100 [00:05<00:03, 10.94it/s]\n 66%|██████▌ | 66/100 [00:06<00:03, 11.06it/s]\n 68%|██████▊ | 68/100 [00:06<00:02, 11.32it/s]\n 70%|███████ | 70/100 [00:06<00:02, 11.27it/s]\n 72%|███████▏ | 72/100 [00:06<00:02, 11.11it/s]\n 74%|███████▍ | 74/100 [00:06<00:02, 11.37it/s]\n 76%|███████▌ | 76/100 [00:06<00:02, 11.55it/s]\n 78%|███████▊ | 78/100 [00:07<00:01, 11.67it/s]\n 80%|████████ | 80/100 [00:07<00:01, 11.44it/s]\n 82%|████████▏ | 82/100 [00:07<00:01, 11.22it/s]\n 84%|████████▍ | 84/100 [00:07<00:01, 10.98it/s]\n 86%|████████▌ | 86/100 [00:07<00:01, 10.92it/s]\n 88%|████████▊ | 88/100 [00:08<00:01, 11.05it/s]\n 90%|█████████ | 90/100 [00:08<00:00, 11.32it/s]\n 92%|█████████▏| 92/100 [00:08<00:00, 11.41it/s]\n 94%|█████████▍| 94/100 [00:08<00:00, 11.38it/s]\n 96%|█████████▌| 96/100 [00:08<00:00, 11.25it/s]\n 98%|█████████▊| 98/100 [00:08<00:00, 11.21it/s]\n100%|██████████| 100/100 [00:09<00:00, 11.31it/s]\n100%|██████████| 100/100 [00:09<00:00, 11.01it/s]", "metrics": { "predict_time": 12.53522, "total_time": 12.500022 }, "output": [ "https://replicate.delivery/pbxt/C3TyPTuH1ALBBZ2IcgAcq7H8c2Ednsep2J14EmXyW3WhDnnIA/out-0.png" ], "started_at": "2023-07-12T22:56:54.813093Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/lokruybbg3jnq3wf6d6v276qa4", "cancel": "https://api.replicate.com/v1/predictions/lokruybbg3jnq3wf6d6v276qa4/cancel" }, "version": "424befb1eae6af8363edb846ae98a11111a39740988baebd279d73fe3ecc92c2" }
Generated inUsing seed: 50269 0%| | 0/25 [00:00<?, ?it/s] 12%|█▏ | 3/25 [00:00<00:00, 28.90it/s] 24%|██▍ | 6/25 [00:00<00:00, 28.75it/s] 36%|███▌ | 9/25 [00:00<00:00, 28.94it/s] 52%|█████▏ | 13/25 [00:00<00:00, 30.29it/s] 68%|██████▊ | 17/25 [00:00<00:00, 32.88it/s] 84%|████████▍ | 21/25 [00:00<00:00, 33.36it/s] 100%|██████████| 25/25 [00:00<00:00, 30.96it/s] 100%|██████████| 25/25 [00:00<00:00, 30.98it/s] The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature'] 0%| | 0/25 [00:00<?, ?it/s] 16%|█▌ | 4/25 [00:00<00:00, 37.45it/s] 32%|███▏ | 8/25 [00:00<00:00, 36.14it/s] 48%|████▊ | 12/25 [00:00<00:00, 33.41it/s] 64%|██████▍ | 16/25 [00:00<00:00, 32.57it/s] 80%|████████ | 20/25 [00:00<00:00, 30.45it/s] 96%|█████████▌| 24/25 [00:00<00:00, 30.95it/s] 100%|██████████| 25/25 [00:00<00:00, 31.65it/s] 0%| | 0/100 [00:00<?, ?it/s] 2%|▏ | 2/100 [00:00<00:09, 10.35it/s] 4%|▍ | 4/100 [00:00<00:08, 10.68it/s] 6%|▌ | 6/100 [00:00<00:08, 10.72it/s] 8%|▊ | 8/100 [00:00<00:08, 10.72it/s] 10%|█ | 10/100 [00:00<00:08, 10.80it/s] 12%|█▏ | 12/100 [00:01<00:08, 10.81it/s] 14%|█▍ | 14/100 [00:01<00:07, 10.86it/s] 16%|█▌ | 16/100 [00:01<00:07, 10.87it/s] 18%|█▊ | 18/100 [00:01<00:07, 10.85it/s] 20%|██ | 20/100 [00:01<00:07, 10.92it/s] 22%|██▏ | 22/100 [00:02<00:07, 10.83it/s] 24%|██▍ | 24/100 [00:02<00:07, 10.69it/s] 26%|██▌ | 26/100 [00:02<00:06, 10.60it/s] 28%|██▊ | 28/100 [00:02<00:06, 10.63it/s] 30%|███ | 30/100 [00:02<00:06, 10.79it/s] 32%|███▏ | 32/100 [00:02<00:06, 10.83it/s] 34%|███▍ | 34/100 [00:03<00:06, 10.69it/s] 36%|███▌ | 36/100 [00:03<00:06, 10.58it/s] 38%|███▊ | 38/100 [00:03<00:05, 10.46it/s] 40%|████ | 40/100 [00:03<00:05, 10.43it/s] 42%|████▏ | 42/100 [00:03<00:05, 10.67it/s] 44%|████▍ | 44/100 [00:04<00:05, 10.95it/s] 46%|████▌ | 46/100 [00:04<00:04, 11.05it/s] 48%|████▊ | 48/100 [00:04<00:04, 11.14it/s] 50%|█████ | 50/100 [00:04<00:04, 11.08it/s] 52%|█████▏ | 52/100 [00:04<00:04, 11.09it/s] 54%|█████▍ | 54/100 [00:04<00:04, 11.09it/s] 56%|█████▌ | 56/100 [00:05<00:03, 11.14it/s] 58%|█████▊ | 58/100 [00:05<00:03, 11.06it/s] 60%|██████ | 60/100 [00:05<00:03, 10.93it/s] 62%|██████▏ | 62/100 [00:05<00:03, 10.97it/s] 64%|██████▍ | 64/100 [00:05<00:03, 10.94it/s] 66%|██████▌ | 66/100 [00:06<00:03, 11.06it/s] 68%|██████▊ | 68/100 [00:06<00:02, 11.32it/s] 70%|███████ | 70/100 [00:06<00:02, 11.27it/s] 72%|███████▏ | 72/100 [00:06<00:02, 11.11it/s] 74%|███████▍ | 74/100 [00:06<00:02, 11.37it/s] 76%|███████▌ | 76/100 [00:06<00:02, 11.55it/s] 78%|███████▊ | 78/100 [00:07<00:01, 11.67it/s] 80%|████████ | 80/100 [00:07<00:01, 11.44it/s] 82%|████████▏ | 82/100 [00:07<00:01, 11.22it/s] 84%|████████▍ | 84/100 [00:07<00:01, 10.98it/s] 86%|████████▌ | 86/100 [00:07<00:01, 10.92it/s] 88%|████████▊ | 88/100 [00:08<00:01, 11.05it/s] 90%|█████████ | 90/100 [00:08<00:00, 11.32it/s] 92%|█████████▏| 92/100 [00:08<00:00, 11.41it/s] 94%|█████████▍| 94/100 [00:08<00:00, 11.38it/s] 96%|█████████▌| 96/100 [00:08<00:00, 11.25it/s] 98%|█████████▊| 98/100 [00:08<00:00, 11.21it/s] 100%|██████████| 100/100 [00:09<00:00, 11.31it/s] 100%|██████████| 100/100 [00:09<00:00, 11.01it/s]
Prediction
ai-forever/kandinsky-2.2:ad9d7879ID4j7qfxrblqjctaabzexar4gquaStatusSucceededSourceWebHardwareA100 (40GB)Total durationCreatedby @chenxwhInput
- width
- "1024"
- height
- 1024
- prompt
- a two year old girl helps a small robot stand up, the photo is realistic, high definition, color image with a park background
- num_outputs
- 1
- negative_prompt
- num_inference_steps
- 200
{ "width": "1024", "height": 1024, "prompt": "a two year old girl helps a small robot stand up, the photo is realistic, high definition, color image with a park background", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 200 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run ai-forever/kandinsky-2.2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ai-forever/kandinsky-2.2:ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", { input: { width: "1024", height: 1024, prompt: "a two year old girl helps a small robot stand up, the photo is realistic, high definition, color image with a park background", num_outputs: 1, negative_prompt: "", num_inference_steps: 200 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run ai-forever/kandinsky-2.2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ai-forever/kandinsky-2.2:ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", input={ "width": "1024", "height": 1024, "prompt": "a two year old girl helps a small robot stand up, the photo is realistic, high definition, color image with a park background", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 200 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run ai-forever/kandinsky-2.2 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": "ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", "input": { "width": "1024", "height": 1024, "prompt": "a two year old girl helps a small robot stand up, the photo is realistic, high definition, color image with a park background", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 200 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-07-12T22:58:56.647910Z", "created_at": "2023-07-12T22:58:35.580426Z", "data_removed": false, "error": null, "id": "4j7qfxrblqjctaabzexar4gqua", "input": { "width": "1024", "height": 1024, "prompt": "a two year old girl helps a small robot stand up, the photo is realistic, high definition, color image with a park background", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 200 }, "logs": "Using seed: 49122\n 0%| | 0/25 [00:00<?, ?it/s]\n 16%|█▌ | 4/25 [00:00<00:00, 39.64it/s]\n 32%|███▏ | 8/25 [00:00<00:00, 39.43it/s]\n 48%|████▊ | 12/25 [00:00<00:00, 39.49it/s]\n 64%|██████▍ | 16/25 [00:00<00:00, 38.84it/s]\n 80%|████████ | 20/25 [00:00<00:00, 35.69it/s]\n 96%|█████████▌| 24/25 [00:00<00:00, 36.57it/s]\n100%|██████████| 25/25 [00:00<00:00, 37.46it/s]\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature']\n 0%| | 0/25 [00:00<?, ?it/s]\n 16%|█▌ | 4/25 [00:00<00:00, 30.81it/s]\n 32%|███▏ | 8/25 [00:00<00:00, 30.98it/s]\n 48%|████▊ | 12/25 [00:00<00:00, 34.11it/s]\n 64%|██████▍ | 16/25 [00:00<00:00, 35.14it/s]\n 80%|████████ | 20/25 [00:00<00:00, 32.94it/s]\n 96%|█████████▌| 24/25 [00:00<00:00, 32.09it/s]\n100%|██████████| 25/25 [00:00<00:00, 32.44it/s]\n 0%| | 0/200 [00:00<?, ?it/s]\n 0%| | 1/200 [00:00<00:20, 9.80it/s]\n 2%|▏ | 3/200 [00:00<00:18, 10.91it/s]\n 2%|▎ | 5/200 [00:00<00:18, 10.76it/s]\n 4%|▎ | 7/200 [00:00<00:17, 10.79it/s]\n 4%|▍ | 9/200 [00:00<00:17, 11.16it/s]\n 6%|▌ | 11/200 [00:00<00:16, 11.33it/s]\n 6%|▋ | 13/200 [00:01<00:16, 11.16it/s]\n 8%|▊ | 15/200 [00:01<00:16, 11.14it/s]\n 8%|▊ | 17/200 [00:01<00:16, 11.20it/s]\n 10%|▉ | 19/200 [00:01<00:16, 11.24it/s]\n 10%|█ | 21/200 [00:01<00:16, 11.11it/s]\n 12%|█▏ | 23/200 [00:02<00:15, 11.15it/s]\n 12%|█▎ | 25/200 [00:02<00:15, 11.09it/s]\n 14%|█▎ | 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Generated inUsing seed: 49122 0%| | 0/25 [00:00<?, ?it/s] 16%|█▌ | 4/25 [00:00<00:00, 39.64it/s] 32%|███▏ | 8/25 [00:00<00:00, 39.43it/s] 48%|████▊ | 12/25 [00:00<00:00, 39.49it/s] 64%|██████▍ | 16/25 [00:00<00:00, 38.84it/s] 80%|████████ | 20/25 [00:00<00:00, 35.69it/s] 96%|█████████▌| 24/25 [00:00<00:00, 36.57it/s] 100%|██████████| 25/25 [00:00<00:00, 37.46it/s] The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature'] 0%| | 0/25 [00:00<?, ?it/s] 16%|█▌ | 4/25 [00:00<00:00, 30.81it/s] 32%|███▏ | 8/25 [00:00<00:00, 30.98it/s] 48%|████▊ | 12/25 [00:00<00:00, 34.11it/s] 64%|██████▍ | 16/25 [00:00<00:00, 35.14it/s] 80%|████████ | 20/25 [00:00<00:00, 32.94it/s] 96%|█████████▌| 24/25 [00:00<00:00, 32.09it/s] 100%|██████████| 25/25 [00:00<00:00, 32.44it/s] 0%| | 0/200 [00:00<?, 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Prediction
ai-forever/kandinsky-2.2:ad9d7879IDazt7kbrbavwnrr3hvfqwhrvebeStatusSucceededSourceWebHardwareA100 (40GB)Total durationCreatedInput
- width
- "1024"
- height
- 1024
- prompt
- glass ball, on a wooden table, fantastic castle, blurry and dreamy illustration, in a miniature country, round window, ornate palace of greenery, whimsical design
- num_outputs
- 1
- negative_prompt
- num_inference_steps
- 100
{ "width": "1024", "height": 1024, "prompt": "glass ball, on a wooden table, fantastic castle, blurry and dreamy illustration, in a miniature country, round window, ornate palace of greenery, whimsical design ", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 100 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run ai-forever/kandinsky-2.2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ai-forever/kandinsky-2.2:ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", { input: { width: "1024", height: 1024, prompt: "glass ball, on a wooden table, fantastic castle, blurry and dreamy illustration, in a miniature country, round window, ornate palace of greenery, whimsical design ", num_outputs: 1, negative_prompt: "", num_inference_steps: 100 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run ai-forever/kandinsky-2.2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ai-forever/kandinsky-2.2:ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", input={ "width": "1024", "height": 1024, "prompt": "glass ball, on a wooden table, fantastic castle, blurry and dreamy illustration, in a miniature country, round window, ornate palace of greenery, whimsical design ", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 100 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run ai-forever/kandinsky-2.2 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": "ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", "input": { "width": "1024", "height": 1024, "prompt": "glass ball, on a wooden table, fantastic castle, blurry and dreamy illustration, in a miniature country, round window, ornate palace of greenery, whimsical design ", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 100 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-07-12T23:01:37.979722Z", "created_at": "2023-07-12T23:01:25.558206Z", "data_removed": false, "error": null, "id": "azt7kbrbavwnrr3hvfqwhrvebe", "input": { "width": "1024", "height": 1024, "prompt": "glass ball, on a wooden table, fantastic castle, blurry and dreamy illustration, in a miniature country, round window, ornate palace of greenery, whimsical design ", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 100 }, "logs": "Using seed: 29924\n 0%| | 0/25 [00:00<?, ?it/s]\n 16%|█▌ | 4/25 [00:00<00:00, 37.66it/s]\n 32%|███▏ | 8/25 [00:00<00:00, 36.71it/s]\n 48%|████▊ | 12/25 [00:00<00:00, 36.69it/s]\n 64%|██████▍ | 16/25 [00:00<00:00, 36.12it/s]\n 80%|████████ | 20/25 [00:00<00:00, 36.35it/s]\n 96%|█████████▌| 24/25 [00:00<00:00, 36.31it/s]\n100%|██████████| 25/25 [00:00<00:00, 36.54it/s]\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature']\n 0%| | 0/25 [00:00<?, ?it/s]\n 16%|█▌ | 4/25 [00:00<00:00, 36.08it/s]\n 32%|███▏ | 8/25 [00:00<00:00, 35.42it/s]\n 48%|████▊ | 12/25 [00:00<00:00, 33.92it/s]\n 64%|██████▍ | 16/25 [00:00<00:00, 33.53it/s]\n 80%|████████ | 20/25 [00:00<00:00, 30.67it/s]\n 96%|█████████▌| 24/25 [00:00<00:00, 29.49it/s]\n100%|██████████| 25/25 [00:00<00:00, 31.06it/s]\n 0%| | 0/100 [00:00<?, ?it/s]\n 1%| | 1/100 [00:00<00:10, 9.41it/s]\n 2%|▏ | 2/100 [00:00<00:10, 9.31it/s]\n 4%|▍ | 4/100 [00:00<00:09, 9.87it/s]\n 6%|▌ | 6/100 [00:00<00:09, 10.33it/s]\n 8%|▊ | 8/100 [00:00<00:08, 10.36it/s]\n 10%|█ | 10/100 [00:00<00:08, 10.36it/s]\n 12%|█▏ | 12/100 [00:01<00:08, 10.57it/s]\n 14%|█▍ | 14/100 [00:01<00:07, 10.82it/s]\n 16%|█▌ | 16/100 [00:01<00:07, 11.09it/s]\n 18%|█▊ | 18/100 [00:01<00:07, 11.23it/s]\n 20%|██ | 20/100 [00:01<00:07, 11.27it/s]\n 22%|██▏ | 22/100 [00:02<00:06, 11.40it/s]\n 24%|██▍ | 24/100 [00:02<00:06, 11.25it/s]\n 26%|██▌ | 26/100 [00:02<00:06, 11.18it/s]\n 28%|██▊ | 28/100 [00:02<00:06, 11.08it/s]\n 30%|███ | 30/100 [00:02<00:06, 11.20it/s]\n 32%|███▏ | 32/100 [00:02<00:06, 11.20it/s]\n 34%|███▍ | 34/100 [00:03<00:05, 11.27it/s]\n 36%|███▌ | 36/100 [00:03<00:05, 11.39it/s]\n 38%|███▊ | 38/100 [00:03<00:05, 11.55it/s]\n 40%|████ | 40/100 [00:03<00:05, 11.68it/s]\n 42%|████▏ | 42/100 [00:03<00:05, 11.59it/s]\n 44%|████▍ | 44/100 [00:03<00:04, 11.70it/s]\n 46%|████▌ | 46/100 [00:04<00:04, 11.77it/s]\n 48%|████▊ | 48/100 [00:04<00:04, 11.83it/s]\n 50%|█████ | 50/100 [00:04<00:04, 11.88it/s]\n 52%|█████▏ | 52/100 [00:04<00:04, 11.83it/s]\n 54%|█████▍ | 54/100 [00:04<00:03, 11.71it/s]\n 56%|█████▌ | 56/100 [00:04<00:03, 11.67it/s]\n 58%|█████▊ | 58/100 [00:05<00:03, 11.65it/s]\n 60%|██████ | 60/100 [00:05<00:03, 11.75it/s]\n 62%|██████▏ | 62/100 [00:05<00:03, 11.71it/s]\n 64%|██████▍ | 64/100 [00:05<00:03, 11.61it/s]\n 66%|██████▌ | 66/100 [00:05<00:02, 11.49it/s]\n 68%|██████▊ | 68/100 [00:06<00:02, 11.64it/s]\n 70%|███████ | 70/100 [00:06<00:02, 11.51it/s]\n 72%|███████▏ | 72/100 [00:06<00:02, 11.55it/s]\n 74%|███████▍ | 74/100 [00:06<00:02, 11.68it/s]\n 76%|███████▌ | 76/100 [00:06<00:02, 11.76it/s]\n 78%|███████▊ | 78/100 [00:06<00:01, 11.77it/s]\n 80%|████████ | 80/100 [00:07<00:01, 11.83it/s]\n 82%|████████▏ | 82/100 [00:07<00:01, 11.87it/s]\n 84%|████████▍ | 84/100 [00:07<00:01, 11.88it/s]\n 86%|████████▌ | 86/100 [00:07<00:01, 11.87it/s]\n 88%|████████▊ | 88/100 [00:07<00:01, 11.44it/s]\n 90%|█████████ | 90/100 [00:07<00:00, 11.19it/s]\n 92%|█████████▏| 92/100 [00:08<00:00, 10.93it/s]\n 94%|█████████▍| 94/100 [00:08<00:00, 10.86it/s]\n 96%|█████████▌| 96/100 [00:08<00:00, 11.12it/s]\n 98%|█████████▊| 98/100 [00:08<00:00, 11.11it/s]\n100%|██████████| 100/100 [00:08<00:00, 10.88it/s]\n100%|██████████| 100/100 [00:08<00:00, 11.33it/s]", "metrics": { "predict_time": 12.449519, "total_time": 12.421516 }, "output": [ "https://replicate.delivery/pbxt/CnQ9S5cCxraIHtueXUUEfe4TyQmHmk9CeMx8g9rwpxWFt48EB/out-0.png" ], "started_at": "2023-07-12T23:01:25.530203Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/azt7kbrbavwnrr3hvfqwhrvebe", "cancel": "https://api.replicate.com/v1/predictions/azt7kbrbavwnrr3hvfqwhrvebe/cancel" }, "version": "424befb1eae6af8363edb846ae98a11111a39740988baebd279d73fe3ecc92c2" }
Generated inUsing seed: 29924 0%| | 0/25 [00:00<?, ?it/s] 16%|█▌ | 4/25 [00:00<00:00, 37.66it/s] 32%|███▏ | 8/25 [00:00<00:00, 36.71it/s] 48%|████▊ | 12/25 [00:00<00:00, 36.69it/s] 64%|██████▍ | 16/25 [00:00<00:00, 36.12it/s] 80%|████████ | 20/25 [00:00<00:00, 36.35it/s] 96%|█████████▌| 24/25 [00:00<00:00, 36.31it/s] 100%|██████████| 25/25 [00:00<00:00, 36.54it/s] The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature'] 0%| | 0/25 [00:00<?, ?it/s] 16%|█▌ | 4/25 [00:00<00:00, 36.08it/s] 32%|███▏ | 8/25 [00:00<00:00, 35.42it/s] 48%|████▊ | 12/25 [00:00<00:00, 33.92it/s] 64%|██████▍ | 16/25 [00:00<00:00, 33.53it/s] 80%|████████ | 20/25 [00:00<00:00, 30.67it/s] 96%|█████████▌| 24/25 [00:00<00:00, 29.49it/s] 100%|██████████| 25/25 [00:00<00:00, 31.06it/s] 0%| | 0/100 [00:00<?, ?it/s] 1%| | 1/100 [00:00<00:10, 9.41it/s] 2%|▏ | 2/100 [00:00<00:10, 9.31it/s] 4%|▍ | 4/100 [00:00<00:09, 9.87it/s] 6%|▌ | 6/100 [00:00<00:09, 10.33it/s] 8%|▊ | 8/100 [00:00<00:08, 10.36it/s] 10%|█ | 10/100 [00:00<00:08, 10.36it/s] 12%|█▏ | 12/100 [00:01<00:08, 10.57it/s] 14%|█▍ | 14/100 [00:01<00:07, 10.82it/s] 16%|█▌ | 16/100 [00:01<00:07, 11.09it/s] 18%|█▊ | 18/100 [00:01<00:07, 11.23it/s] 20%|██ | 20/100 [00:01<00:07, 11.27it/s] 22%|██▏ | 22/100 [00:02<00:06, 11.40it/s] 24%|██▍ | 24/100 [00:02<00:06, 11.25it/s] 26%|██▌ | 26/100 [00:02<00:06, 11.18it/s] 28%|██▊ | 28/100 [00:02<00:06, 11.08it/s] 30%|███ | 30/100 [00:02<00:06, 11.20it/s] 32%|███▏ | 32/100 [00:02<00:06, 11.20it/s] 34%|███▍ | 34/100 [00:03<00:05, 11.27it/s] 36%|███▌ | 36/100 [00:03<00:05, 11.39it/s] 38%|███▊ | 38/100 [00:03<00:05, 11.55it/s] 40%|████ | 40/100 [00:03<00:05, 11.68it/s] 42%|████▏ | 42/100 [00:03<00:05, 11.59it/s] 44%|████▍ | 44/100 [00:03<00:04, 11.70it/s] 46%|████▌ | 46/100 [00:04<00:04, 11.77it/s] 48%|████▊ | 48/100 [00:04<00:04, 11.83it/s] 50%|█████ | 50/100 [00:04<00:04, 11.88it/s] 52%|█████▏ | 52/100 [00:04<00:04, 11.83it/s] 54%|█████▍ | 54/100 [00:04<00:03, 11.71it/s] 56%|█████▌ | 56/100 [00:04<00:03, 11.67it/s] 58%|█████▊ | 58/100 [00:05<00:03, 11.65it/s] 60%|██████ | 60/100 [00:05<00:03, 11.75it/s] 62%|██████▏ | 62/100 [00:05<00:03, 11.71it/s] 64%|██████▍ | 64/100 [00:05<00:03, 11.61it/s] 66%|██████▌ | 66/100 [00:05<00:02, 11.49it/s] 68%|██████▊ | 68/100 [00:06<00:02, 11.64it/s] 70%|███████ | 70/100 [00:06<00:02, 11.51it/s] 72%|███████▏ | 72/100 [00:06<00:02, 11.55it/s] 74%|███████▍ | 74/100 [00:06<00:02, 11.68it/s] 76%|███████▌ | 76/100 [00:06<00:02, 11.76it/s] 78%|███████▊ | 78/100 [00:06<00:01, 11.77it/s] 80%|████████ | 80/100 [00:07<00:01, 11.83it/s] 82%|████████▏ | 82/100 [00:07<00:01, 11.87it/s] 84%|████████▍ | 84/100 [00:07<00:01, 11.88it/s] 86%|████████▌ | 86/100 [00:07<00:01, 11.87it/s] 88%|████████▊ | 88/100 [00:07<00:01, 11.44it/s] 90%|█████████ | 90/100 [00:07<00:00, 11.19it/s] 92%|█████████▏| 92/100 [00:08<00:00, 10.93it/s] 94%|█████████▍| 94/100 [00:08<00:00, 10.86it/s] 96%|█████████▌| 96/100 [00:08<00:00, 11.12it/s] 98%|█████████▊| 98/100 [00:08<00:00, 11.11it/s] 100%|██████████| 100/100 [00:08<00:00, 10.88it/s] 100%|██████████| 100/100 [00:08<00:00, 11.33it/s]
Prediction
ai-forever/kandinsky-2.2:ad9d7879IDk66b4fjbdlgk7zev2vflert2yyStatusSucceededSourceWebHardwareA100 (40GB)Total durationCreatedInput
- width
- "1024"
- height
- 1024
- prompt
- watercolor mixed media masterpiece beautiful white cozy house with chimneys, a purple door, richly decorated with lupine, flower pots overgrown with moss, Provence, gold accents, shabby chic style, isolated on white, extremely photorealistic details, realistic high detail, high resolution
- num_outputs
- 1
- negative_prompt
- num_inference_steps
- 100
{ "width": "1024", "height": 1024, "prompt": "watercolor mixed media masterpiece beautiful white cozy house with chimneys, a purple door, richly decorated with lupine, flower pots overgrown with moss, Provence, gold accents, shabby chic style, isolated on white, extremely photorealistic details, realistic high detail, high resolution ", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 100 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run ai-forever/kandinsky-2.2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ai-forever/kandinsky-2.2:ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", { input: { width: "1024", height: 1024, prompt: "watercolor mixed media masterpiece beautiful white cozy house with chimneys, a purple door, richly decorated with lupine, flower pots overgrown with moss, Provence, gold accents, shabby chic style, isolated on white, extremely photorealistic details, realistic high detail, high resolution ", num_outputs: 1, negative_prompt: "", num_inference_steps: 100 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run ai-forever/kandinsky-2.2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ai-forever/kandinsky-2.2:ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", input={ "width": "1024", "height": 1024, "prompt": "watercolor mixed media masterpiece beautiful white cozy house with chimneys, a purple door, richly decorated with lupine, flower pots overgrown with moss, Provence, gold accents, shabby chic style, isolated on white, extremely photorealistic details, realistic high detail, high resolution ", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 100 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run ai-forever/kandinsky-2.2 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": "ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a", "input": { "width": "1024", "height": 1024, "prompt": "watercolor mixed media masterpiece beautiful white cozy house with chimneys, a purple door, richly decorated with lupine, flower pots overgrown with moss, Provence, gold accents, shabby chic style, isolated on white, extremely photorealistic details, realistic high detail, high resolution ", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 100 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-07-12T23:06:06.878257Z", "created_at": "2023-07-12T23:05:54.530732Z", "data_removed": false, "error": null, "id": "k66b4fjbdlgk7zev2vflert2yy", "input": { "width": "1024", "height": 1024, "prompt": "watercolor mixed media masterpiece beautiful white cozy house with chimneys, a purple door, richly decorated with lupine, flower pots overgrown with moss, Provence, gold accents, shabby chic style, isolated on white, extremely photorealistic details, realistic high detail, high resolution ", "num_outputs": 1, "negative_prompt": "", "num_inference_steps": 100 }, "logs": "Using seed: 12970\n 0%| | 0/25 [00:00<?, ?it/s]\n 16%|█▌ | 4/25 [00:00<00:00, 38.50it/s]\n 32%|███▏ | 8/25 [00:00<00:00, 30.56it/s]\n 48%|████▊ | 12/25 [00:00<00:00, 34.11it/s]\n 64%|██████▍ | 16/25 [00:00<00:00, 35.64it/s]\n 80%|████████ | 20/25 [00:00<00:00, 34.16it/s]\n 96%|█████████▌| 24/25 [00:00<00:00, 33.02it/s]\n100%|██████████| 25/25 [00:00<00:00, 33.76it/s]\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature']\n 0%| | 0/25 [00:00<?, ?it/s]\n 12%|█▏ | 3/25 [00:00<00:00, 27.22it/s]\n 28%|██▊ | 7/25 [00:00<00:00, 31.73it/s]\n 44%|████▍ | 11/25 [00:00<00:00, 32.46it/s]\n 60%|██████ | 15/25 [00:00<00:00, 31.66it/s]\n 76%|███████▌ | 19/25 [00:00<00:00, 31.53it/s]\n 92%|█████████▏| 23/25 [00:00<00:00, 33.00it/s]\n100%|██████████| 25/25 [00:00<00:00, 32.25it/s]\n 0%| | 0/100 [00:00<?, ?it/s]\n 1%| | 1/100 [00:00<00:10, 9.83it/s]\n 3%|▎ | 3/100 [00:00<00:09, 10.71it/s]\n 5%|▌ | 5/100 [00:00<00:08, 11.12it/s]\n 7%|▋ | 7/100 [00:00<00:08, 11.07it/s]\n 9%|▉ | 9/100 [00:00<00:08, 10.66it/s]\n 11%|█ | 11/100 [00:01<00:08, 10.62it/s]\n 13%|█▎ | 13/100 [00:01<00:08, 10.51it/s]\n 15%|█▌ | 15/100 [00:01<00:08, 10.61it/s]\n 17%|█▋ | 17/100 [00:01<00:07, 10.71it/s]\n 19%|█▉ | 19/100 [00:01<00:07, 10.78it/s]\n 21%|██ | 21/100 [00:01<00:07, 10.88it/s]\n 23%|██▎ | 23/100 [00:02<00:07, 10.95it/s]\n 25%|██▌ | 25/100 [00:02<00:06, 10.83it/s]\n 27%|██▋ | 27/100 [00:02<00:06, 11.06it/s]\n 29%|██▉ | 29/100 [00:02<00:06, 11.07it/s]\n 31%|███ | 31/100 [00:02<00:06, 10.92it/s]\n 33%|███▎ | 33/100 [00:03<00:06, 10.83it/s]\n 35%|███▌ | 35/100 [00:03<00:05, 11.10it/s]\n 37%|███▋ | 37/100 [00:03<00:05, 11.35it/s]\n 39%|███▉ | 39/100 [00:03<00:05, 11.55it/s]\n 41%|████ | 41/100 [00:03<00:05, 11.63it/s]\n 43%|████▎ | 43/100 [00:03<00:04, 11.64it/s]\n 45%|████▌ | 45/100 [00:04<00:04, 11.71it/s]\n 47%|████▋ | 47/100 [00:04<00:04, 11.49it/s]\n 49%|████▉ | 49/100 [00:04<00:04, 11.30it/s]\n 51%|█████ | 51/100 [00:04<00:04, 11.24it/s]\n 53%|█████▎ | 53/100 [00:04<00:04, 11.01it/s]\n 55%|█████▌ | 55/100 [00:04<00:04, 10.85it/s]\n 57%|█████▋ | 57/100 [00:05<00:04, 10.65it/s]\n 59%|█████▉ | 59/100 [00:05<00:03, 10.60it/s]\n 61%|██████ | 61/100 [00:05<00:03, 10.67it/s]\n 63%|██████▎ | 63/100 [00:05<00:03, 10.72it/s]\n 65%|██████▌ | 65/100 [00:05<00:03, 10.77it/s]\n 67%|██████▋ | 67/100 [00:06<00:03, 10.92it/s]\n 69%|██████▉ | 69/100 [00:06<00:02, 10.83it/s]\n 71%|███████ | 71/100 [00:06<00:02, 10.61it/s]\n 73%|███████▎ | 73/100 [00:06<00:02, 10.45it/s]\n 75%|███████▌ | 75/100 [00:06<00:02, 10.32it/s]\n 77%|███████▋ | 77/100 [00:07<00:02, 10.37it/s]\n 79%|███████▉ | 79/100 [00:07<00:01, 10.74it/s]\n 81%|████████ | 81/100 [00:07<00:01, 10.97it/s]\n 83%|████████▎ | 83/100 [00:07<00:01, 11.01it/s]\n 85%|████████▌ | 85/100 [00:07<00:01, 10.84it/s]\n 87%|████████▋ | 87/100 [00:07<00:01, 10.86it/s]\n 89%|████████▉ | 89/100 [00:08<00:01, 10.71it/s]\n 91%|█████████ | 91/100 [00:08<00:00, 10.61it/s]\n 93%|█████████▎| 93/100 [00:08<00:00, 10.68it/s]\n 95%|█████████▌| 95/100 [00:08<00:00, 10.66it/s]\n 97%|█████████▋| 97/100 [00:08<00:00, 10.36it/s]\n 99%|█████████▉| 99/100 [00:09<00:00, 10.19it/s]\n100%|██████████| 100/100 [00:09<00:00, 10.81it/s]", "metrics": { "predict_time": 12.384828, "total_time": 12.347525 }, "output": [ "https://replicate.delivery/pbxt/yllavn6d5pZtIl2X17lkx6MdKVKzAvb8Sp9rWrecUcDvHnnIA/out-0.png" ], "started_at": "2023-07-12T23:05:54.493429Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/k66b4fjbdlgk7zev2vflert2yy", "cancel": "https://api.replicate.com/v1/predictions/k66b4fjbdlgk7zev2vflert2yy/cancel" }, "version": "424befb1eae6af8363edb846ae98a11111a39740988baebd279d73fe3ecc92c2" }
Generated inUsing seed: 12970 0%| | 0/25 [00:00<?, ?it/s] 16%|█▌ | 4/25 [00:00<00:00, 38.50it/s] 32%|███▏ | 8/25 [00:00<00:00, 30.56it/s] 48%|████▊ | 12/25 [00:00<00:00, 34.11it/s] 64%|██████▍ | 16/25 [00:00<00:00, 35.64it/s] 80%|████████ | 20/25 [00:00<00:00, 34.16it/s] 96%|█████████▌| 24/25 [00:00<00:00, 33.02it/s] 100%|██████████| 25/25 [00:00<00:00, 33.76it/s] The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature'] 0%| | 0/25 [00:00<?, ?it/s] 12%|█▏ | 3/25 [00:00<00:00, 27.22it/s] 28%|██▊ | 7/25 [00:00<00:00, 31.73it/s] 44%|████▍ | 11/25 [00:00<00:00, 32.46it/s] 60%|██████ | 15/25 [00:00<00:00, 31.66it/s] 76%|███████▌ | 19/25 [00:00<00:00, 31.53it/s] 92%|█████████▏| 23/25 [00:00<00:00, 33.00it/s] 100%|██████████| 25/25 [00:00<00:00, 32.25it/s] 0%| | 0/100 [00:00<?, ?it/s] 1%| | 1/100 [00:00<00:10, 9.83it/s] 3%|▎ | 3/100 [00:00<00:09, 10.71it/s] 5%|▌ | 5/100 [00:00<00:08, 11.12it/s] 7%|▋ | 7/100 [00:00<00:08, 11.07it/s] 9%|▉ | 9/100 [00:00<00:08, 10.66it/s] 11%|█ | 11/100 [00:01<00:08, 10.62it/s] 13%|█▎ | 13/100 [00:01<00:08, 10.51it/s] 15%|█▌ | 15/100 [00:01<00:08, 10.61it/s] 17%|█▋ | 17/100 [00:01<00:07, 10.71it/s] 19%|█▉ | 19/100 [00:01<00:07, 10.78it/s] 21%|██ | 21/100 [00:01<00:07, 10.88it/s] 23%|██▎ | 23/100 [00:02<00:07, 10.95it/s] 25%|██▌ | 25/100 [00:02<00:06, 10.83it/s] 27%|██▋ | 27/100 [00:02<00:06, 11.06it/s] 29%|██▉ | 29/100 [00:02<00:06, 11.07it/s] 31%|███ | 31/100 [00:02<00:06, 10.92it/s] 33%|███▎ | 33/100 [00:03<00:06, 10.83it/s] 35%|███▌ | 35/100 [00:03<00:05, 11.10it/s] 37%|███▋ | 37/100 [00:03<00:05, 11.35it/s] 39%|███▉ | 39/100 [00:03<00:05, 11.55it/s] 41%|████ | 41/100 [00:03<00:05, 11.63it/s] 43%|████▎ | 43/100 [00:03<00:04, 11.64it/s] 45%|████▌ | 45/100 [00:04<00:04, 11.71it/s] 47%|████▋ | 47/100 [00:04<00:04, 11.49it/s] 49%|████▉ | 49/100 [00:04<00:04, 11.30it/s] 51%|█████ | 51/100 [00:04<00:04, 11.24it/s] 53%|█████▎ | 53/100 [00:04<00:04, 11.01it/s] 55%|█████▌ | 55/100 [00:04<00:04, 10.85it/s] 57%|█████▋ | 57/100 [00:05<00:04, 10.65it/s] 59%|█████▉ | 59/100 [00:05<00:03, 10.60it/s] 61%|██████ | 61/100 [00:05<00:03, 10.67it/s] 63%|██████▎ | 63/100 [00:05<00:03, 10.72it/s] 65%|██████▌ | 65/100 [00:05<00:03, 10.77it/s] 67%|██████▋ | 67/100 [00:06<00:03, 10.92it/s] 69%|██████▉ | 69/100 [00:06<00:02, 10.83it/s] 71%|███████ | 71/100 [00:06<00:02, 10.61it/s] 73%|███████▎ | 73/100 [00:06<00:02, 10.45it/s] 75%|███████▌ | 75/100 [00:06<00:02, 10.32it/s] 77%|███████▋ | 77/100 [00:07<00:02, 10.37it/s] 79%|███████▉ | 79/100 [00:07<00:01, 10.74it/s] 81%|████████ | 81/100 [00:07<00:01, 10.97it/s] 83%|████████▎ | 83/100 [00:07<00:01, 11.01it/s] 85%|████████▌ | 85/100 [00:07<00:01, 10.84it/s] 87%|████████▋ | 87/100 [00:07<00:01, 10.86it/s] 89%|████████▉ | 89/100 [00:08<00:01, 10.71it/s] 91%|█████████ | 91/100 [00:08<00:00, 10.61it/s] 93%|█████████▎| 93/100 [00:08<00:00, 10.68it/s] 95%|█████████▌| 95/100 [00:08<00:00, 10.66it/s] 97%|█████████▋| 97/100 [00:08<00:00, 10.36it/s] 99%|█████████▉| 99/100 [00:09<00:00, 10.19it/s] 100%|██████████| 100/100 [00:09<00:00, 10.81it/s]
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