Readme
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Run this model in Node.js with one line of code:
npm install replicate
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import Replicate from "replicate";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run shubhamg1242/coco-ai using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"shubhamg1242/coco-ai:815ed0566474f2ae4de9c648dc21c521d94d6800dd05ab5a697c25fe14355241",
{
input: {
model: "dev",
prompt: "'coco-ai', a beautiful girl in office clicking selfies",
go_fast: true,
lora_scale: 1,
megapixels: "1",
num_outputs: 4,
aspect_ratio: "1:1",
output_format: "webp",
guidance_scale: 3,
output_quality: 81,
prompt_strength: 0.8,
extra_lora_scale: 1,
num_inference_steps: 28
}
}
);
// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"
// To write the file to disk:
fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import replicate
Run shubhamg1242/coco-ai using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"shubhamg1242/coco-ai:815ed0566474f2ae4de9c648dc21c521d94d6800dd05ab5a697c25fe14355241",
input={
"model": "dev",
"prompt": "'coco-ai', a beautiful girl in office clicking selfies",
"go_fast": True,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 4,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3,
"output_quality": 81,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 28
}
)
# To access the file URL:
print(output[0].url())
#=> "http://example.com"
# To write the file to disk:
with open("my-image.png", "wb") as file:
file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run shubhamg1242/coco-ai 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": "shubhamg1242/coco-ai:815ed0566474f2ae4de9c648dc21c521d94d6800dd05ab5a697c25fe14355241",
"input": {
"model": "dev",
"prompt": "\'coco-ai\', a beautiful girl in office clicking selfies",
"go_fast": true,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 4,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3,
"output_quality": 81,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 28
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Add a payment method to run this model.
By signing in, you agree to our
terms of service and privacy policy
{
"completed_at": "2024-11-29T02:25:22.005527Z",
"created_at": "2024-11-29T02:24:31.703000Z",
"data_removed": false,
"error": null,
"id": "wyym6dzhtxrme0ckepxtc3zttm",
"input": {
"model": "dev",
"prompt": "'coco-ai', a beautiful girl in office clicking selfies",
"go_fast": true,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 4,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3,
"output_quality": 81,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 28
},
"logs": "2024-11-29 02:25:02.302 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys\n2024-11-29 02:25:02.303 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 12925.96it/s]\n2024-11-29 02:25:02.327 | SUCCESS | fp8.lora_loading:unload_loras:559 - LoRAs unloaded in 0.024s\nfree=29194703319040\nDownloading weights\n2024-11-29T02:25:02Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpggxvk218/weights url=https://replicate.delivery/xezq/ifip4ExlTDVBGyPbqHUQb6IGIUDCGqfnVpem4ak99RzMwWrnA/trained_model.tar\n2024-11-29T02:25:08Z | INFO | [ Complete ] dest=/tmp/tmpggxvk218/weights size=\"172 MB\" total_elapsed=6.011s url=https://replicate.delivery/xezq/ifip4ExlTDVBGyPbqHUQb6IGIUDCGqfnVpem4ak99RzMwWrnA/trained_model.tar\nDownloaded weights in 6.04s\n2024-11-29 02:25:08.365 | INFO | fp8.lora_loading:convert_lora_weights:493 - Loading LoRA weights for /src/weights-cache/124cab2127c331c6\n2024-11-29 02:25:08.441 | INFO | fp8.lora_loading:convert_lora_weights:514 - LoRA weights loaded\n2024-11-29 02:25:08.441 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys\n2024-11-29 02:25:08.441 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 41%|████ | 125/304 [00:00<00:00, 1243.51it/s]\nApplying LoRA: 82%|████████▏ | 250/304 [00:00<00:00, 992.28it/s] \nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 964.92it/s]\n2024-11-29 02:25:08.756 | SUCCESS | fp8.lora_loading:load_lora:534 - LoRA applied in 0.39s\nrunning quantized prediction\nUsing seed: 3905691338\n 0%| | 0/28 [00:00<?, ?it/s]\n 7%|▋ | 2/28 [00:00<00:01, 18.17it/s]\n 14%|█▍ | 4/28 [00:00<00:01, 13.54it/s]\n 21%|██▏ | 6/28 [00:00<00:01, 12.57it/s]\n 29%|██▊ | 8/28 [00:00<00:01, 12.11it/s]\n 36%|███▌ | 10/28 [00:00<00:01, 11.87it/s]\n 43%|████▎ | 12/28 [00:00<00:01, 11.51it/s]\n 50%|█████ | 14/28 [00:01<00:01, 11.45it/s]\n 57%|█████▋ | 16/28 [00:01<00:01, 11.43it/s]\n 64%|██████▍ | 18/28 [00:01<00:00, 11.44it/s]\n 71%|███████▏ | 20/28 [00:01<00:00, 11.47it/s]\n 79%|███████▊ | 22/28 [00:01<00:00, 11.41it/s]\n 86%|████████▌ | 24/28 [00:02<00:00, 11.33it/s]\n 93%|█████████▎| 26/28 [00:02<00:00, 11.32it/s]\n100%|██████████| 28/28 [00:02<00:00, 11.34it/s]\n100%|██████████| 28/28 [00:02<00:00, 11.67it/s]\n 0%| | 0/28 [00:00<?, ?it/s]\n 7%|▋ | 2/28 [00:00<00:02, 11.60it/s]\n 14%|█▍ | 4/28 [00:00<00:02, 11.50it/s]\n 21%|██▏ | 6/28 [00:00<00:01, 11.38it/s]\n 29%|██▊ | 8/28 [00:00<00:01, 11.30it/s]\n 36%|███▌ | 10/28 [00:00<00:01, 11.31it/s]\n 43%|████▎ | 12/28 [00:01<00:01, 11.36it/s]\n 50%|█████ | 14/28 [00:01<00:01, 11.39it/s]\n 57%|█████▋ | 16/28 [00:01<00:01, 11.38it/s]\n 64%|██████▍ | 18/28 [00:01<00:00, 11.33it/s]\n 71%|███████▏ | 20/28 [00:01<00:00, 11.32it/s]\n 79%|███████▊ | 22/28 [00:01<00:00, 11.33it/s]\n 86%|████████▌ | 24/28 [00:02<00:00, 11.35it/s]\n 93%|█████████▎| 26/28 [00:02<00:00, 11.36it/s]\n100%|██████████| 28/28 [00:02<00:00, 11.39it/s]\n100%|██████████| 28/28 [00:02<00:00, 11.37it/s]\n 0%| | 0/28 [00:00<?, ?it/s]\n 7%|▋ | 2/28 [00:00<00:02, 11.30it/s]\n 14%|█▍ | 4/28 [00:00<00:02, 11.27it/s]\n 21%|██▏ | 6/28 [00:00<00:01, 11.32it/s]\n 29%|██▊ | 8/28 [00:00<00:01, 11.35it/s]\n 36%|███▌ | 10/28 [00:00<00:01, 11.37it/s]\n 43%|████▎ | 12/28 [00:01<00:01, 11.35it/s]\n 50%|█████ | 14/28 [00:01<00:01, 11.33it/s]\n 57%|█████▋ | 16/28 [00:01<00:01, 11.33it/s]\n 64%|██████▍ | 18/28 [00:01<00:00, 11.34it/s]\n 71%|███████▏ | 20/28 [00:01<00:00, 11.34it/s]\n 79%|███████▊ | 22/28 [00:01<00:00, 11.36it/s]\n 86%|████████▌ | 24/28 [00:02<00:00, 11.35it/s]\n 93%|█████████▎| 26/28 [00:02<00:00, 11.33it/s]\n100%|██████████| 28/28 [00:02<00:00, 11.33it/s]\n100%|██████████| 28/28 [00:02<00:00, 11.33it/s]\n 0%| | 0/28 [00:00<?, ?it/s]\n 7%|▋ | 2/28 [00:00<00:02, 11.38it/s]\n 14%|█▍ | 4/28 [00:00<00:02, 11.35it/s]\n 21%|██▏ | 6/28 [00:00<00:01, 11.32it/s]\n 29%|██▊ | 8/28 [00:00<00:01, 11.31it/s]\n 36%|███▌ | 10/28 [00:00<00:01, 11.33it/s]\n 43%|████▎ | 12/28 [00:01<00:01, 11.34it/s]\n 50%|█████ | 14/28 [00:01<00:01, 11.33it/s]\n 57%|█████▋ | 16/28 [00:01<00:01, 11.32it/s]\n 64%|██████▍ | 18/28 [00:01<00:00, 11.32it/s]\n 71%|███████▏ | 20/28 [00:01<00:00, 11.33it/s]\n 79%|███████▊ | 22/28 [00:01<00:00, 11.33it/s]\n 86%|████████▌ | 24/28 [00:02<00:00, 11.34it/s]\n 93%|█████████▎| 26/28 [00:02<00:00, 11.33it/s]\n100%|██████████| 28/28 [00:02<00:00, 11.32it/s]\n100%|██████████| 28/28 [00:02<00:00, 11.32it/s]\nTotal safe images: 4 out of 4",
"metrics": {
"predict_time": 19.701747267000002,
"total_time": 50.302527
},
"output": [
"https://replicate.delivery/xezq/tHY9cOT6IA4rPRoSXCdtoHpGJXZTermqDcWzw7kJUqtIw26JA/out-0.webp",
"https://replicate.delivery/xezq/DirkPNLdr8pVLN6YZTgROBdf4jxohMQXxd8bx84vav7Iw26JA/out-1.webp",
"https://replicate.delivery/xezq/9VDb9vergTVxKKDxI7SHOQAFT2b8i1deHfoZiHz7f0QHB2WPB/out-2.webp",
"https://replicate.delivery/xezq/xiDJWecoQb2xTiPLAOEgLFeaceDM1qv32ZuGPoy9G0fIB2WPB/out-3.webp"
],
"started_at": "2024-11-29T02:25:02.303779Z",
"status": "succeeded",
"urls": {
"stream": "https://stream.replicate.com/v1/files/bcwr-dlo4kyp7cr5i7ic5xcsrndz3idffe2cw4kxpvgi6x5puiaykuyjq",
"get": "https://api.replicate.com/v1/predictions/wyym6dzhtxrme0ckepxtc3zttm",
"cancel": "https://api.replicate.com/v1/predictions/wyym6dzhtxrme0ckepxtc3zttm/cancel"
},
"version": "815ed0566474f2ae4de9c648dc21c521d94d6800dd05ab5a697c25fe14355241"
}
2024-11-29 02:25:02.302 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys
2024-11-29 02:25:02.303 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted
Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 12925.96it/s]
2024-11-29 02:25:02.327 | SUCCESS | fp8.lora_loading:unload_loras:559 - LoRAs unloaded in 0.024s
free=29194703319040
Downloading weights
2024-11-29T02:25:02Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpggxvk218/weights url=https://replicate.delivery/xezq/ifip4ExlTDVBGyPbqHUQb6IGIUDCGqfnVpem4ak99RzMwWrnA/trained_model.tar
2024-11-29T02:25:08Z | INFO | [ Complete ] dest=/tmp/tmpggxvk218/weights size="172 MB" total_elapsed=6.011s url=https://replicate.delivery/xezq/ifip4ExlTDVBGyPbqHUQb6IGIUDCGqfnVpem4ak99RzMwWrnA/trained_model.tar
Downloaded weights in 6.04s
2024-11-29 02:25:08.365 | INFO | fp8.lora_loading:convert_lora_weights:493 - Loading LoRA weights for /src/weights-cache/124cab2127c331c6
2024-11-29 02:25:08.441 | INFO | fp8.lora_loading:convert_lora_weights:514 - LoRA weights loaded
2024-11-29 02:25:08.441 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys
2024-11-29 02:25:08.441 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted
Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s]
Applying LoRA: 41%|████ | 125/304 [00:00<00:00, 1243.51it/s]
Applying LoRA: 82%|████████▏ | 250/304 [00:00<00:00, 992.28it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 964.92it/s]
2024-11-29 02:25:08.756 | SUCCESS | fp8.lora_loading:load_lora:534 - LoRA applied in 0.39s
running quantized prediction
Using seed: 3905691338
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64%|██████▍ | 18/28 [00:01<00:00, 11.32it/s]
71%|███████▏ | 20/28 [00:01<00:00, 11.33it/s]
79%|███████▊ | 22/28 [00:01<00:00, 11.33it/s]
86%|████████▌ | 24/28 [00:02<00:00, 11.34it/s]
93%|█████████▎| 26/28 [00:02<00:00, 11.33it/s]
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100%|██████████| 28/28 [00:02<00:00, 11.32it/s]
Total safe images: 4 out of 4
This model runs on Nvidia H100 GPU hardware. We don't yet have enough runs of this model to provide performance information.
This model doesn't have a readme.
This model is booted and ready for API calls.
This model runs on H100 hardware which costs $0.001525 per second
Choose a file from your machine
Hint: you can also drag files onto the input
Choose a file from your machine
Hint: you can also drag files onto the input
2024-11-29 02:25:02.302 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys
2024-11-29 02:25:02.303 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted
Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 12925.96it/s]
2024-11-29 02:25:02.327 | SUCCESS | fp8.lora_loading:unload_loras:559 - LoRAs unloaded in 0.024s
free=29194703319040
Downloading weights
2024-11-29T02:25:02Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpggxvk218/weights url=https://replicate.delivery/xezq/ifip4ExlTDVBGyPbqHUQb6IGIUDCGqfnVpem4ak99RzMwWrnA/trained_model.tar
2024-11-29T02:25:08Z | INFO | [ Complete ] dest=/tmp/tmpggxvk218/weights size="172 MB" total_elapsed=6.011s url=https://replicate.delivery/xezq/ifip4ExlTDVBGyPbqHUQb6IGIUDCGqfnVpem4ak99RzMwWrnA/trained_model.tar
Downloaded weights in 6.04s
2024-11-29 02:25:08.365 | INFO | fp8.lora_loading:convert_lora_weights:493 - Loading LoRA weights for /src/weights-cache/124cab2127c331c6
2024-11-29 02:25:08.441 | INFO | fp8.lora_loading:convert_lora_weights:514 - LoRA weights loaded
2024-11-29 02:25:08.441 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys
2024-11-29 02:25:08.441 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted
Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s]
Applying LoRA: 41%|████ | 125/304 [00:00<00:00, 1243.51it/s]
Applying LoRA: 82%|████████▏ | 250/304 [00:00<00:00, 992.28it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 964.92it/s]
2024-11-29 02:25:08.756 | SUCCESS | fp8.lora_loading:load_lora:534 - LoRA applied in 0.39s
running quantized prediction
Using seed: 3905691338
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14%|█▍ | 4/28 [00:00<00:01, 13.54it/s]
21%|██▏ | 6/28 [00:00<00:01, 12.57it/s]
29%|██▊ | 8/28 [00:00<00:01, 12.11it/s]
36%|███▌ | 10/28 [00:00<00:01, 11.87it/s]
43%|████▎ | 12/28 [00:00<00:01, 11.51it/s]
50%|█████ | 14/28 [00:01<00:01, 11.45it/s]
57%|█████▋ | 16/28 [00:01<00:01, 11.43it/s]
64%|██████▍ | 18/28 [00:01<00:00, 11.44it/s]
71%|███████▏ | 20/28 [00:01<00:00, 11.47it/s]
79%|███████▊ | 22/28 [00:01<00:00, 11.41it/s]
86%|████████▌ | 24/28 [00:02<00:00, 11.33it/s]
93%|█████████▎| 26/28 [00:02<00:00, 11.32it/s]
100%|██████████| 28/28 [00:02<00:00, 11.34it/s]
100%|██████████| 28/28 [00:02<00:00, 11.67it/s]
0%| | 0/28 [00:00<?, ?it/s]
7%|▋ | 2/28 [00:00<00:02, 11.60it/s]
14%|█▍ | 4/28 [00:00<00:02, 11.50it/s]
21%|██▏ | 6/28 [00:00<00:01, 11.38it/s]
29%|██▊ | 8/28 [00:00<00:01, 11.30it/s]
36%|███▌ | 10/28 [00:00<00:01, 11.31it/s]
43%|████▎ | 12/28 [00:01<00:01, 11.36it/s]
50%|█████ | 14/28 [00:01<00:01, 11.39it/s]
57%|█████▋ | 16/28 [00:01<00:01, 11.38it/s]
64%|██████▍ | 18/28 [00:01<00:00, 11.33it/s]
71%|███████▏ | 20/28 [00:01<00:00, 11.32it/s]
79%|███████▊ | 22/28 [00:01<00:00, 11.33it/s]
86%|████████▌ | 24/28 [00:02<00:00, 11.35it/s]
93%|█████████▎| 26/28 [00:02<00:00, 11.36it/s]
100%|██████████| 28/28 [00:02<00:00, 11.39it/s]
100%|██████████| 28/28 [00:02<00:00, 11.37it/s]
0%| | 0/28 [00:00<?, ?it/s]
7%|▋ | 2/28 [00:00<00:02, 11.30it/s]
14%|█▍ | 4/28 [00:00<00:02, 11.27it/s]
21%|██▏ | 6/28 [00:00<00:01, 11.32it/s]
29%|██▊ | 8/28 [00:00<00:01, 11.35it/s]
36%|███▌ | 10/28 [00:00<00:01, 11.37it/s]
43%|████▎ | 12/28 [00:01<00:01, 11.35it/s]
50%|█████ | 14/28 [00:01<00:01, 11.33it/s]
57%|█████▋ | 16/28 [00:01<00:01, 11.33it/s]
64%|██████▍ | 18/28 [00:01<00:00, 11.34it/s]
71%|███████▏ | 20/28 [00:01<00:00, 11.34it/s]
79%|███████▊ | 22/28 [00:01<00:00, 11.36it/s]
86%|████████▌ | 24/28 [00:02<00:00, 11.35it/s]
93%|█████████▎| 26/28 [00:02<00:00, 11.33it/s]
100%|██████████| 28/28 [00:02<00:00, 11.33it/s]
100%|██████████| 28/28 [00:02<00:00, 11.33it/s]
0%| | 0/28 [00:00<?, ?it/s]
7%|▋ | 2/28 [00:00<00:02, 11.38it/s]
14%|█▍ | 4/28 [00:00<00:02, 11.35it/s]
21%|██▏ | 6/28 [00:00<00:01, 11.32it/s]
29%|██▊ | 8/28 [00:00<00:01, 11.31it/s]
36%|███▌ | 10/28 [00:00<00:01, 11.33it/s]
43%|████▎ | 12/28 [00:01<00:01, 11.34it/s]
50%|█████ | 14/28 [00:01<00:01, 11.33it/s]
57%|█████▋ | 16/28 [00:01<00:01, 11.32it/s]
64%|██████▍ | 18/28 [00:01<00:00, 11.32it/s]
71%|███████▏ | 20/28 [00:01<00:00, 11.33it/s]
79%|███████▊ | 22/28 [00:01<00:00, 11.33it/s]
86%|████████▌ | 24/28 [00:02<00:00, 11.34it/s]
93%|█████████▎| 26/28 [00:02<00:00, 11.33it/s]
100%|██████████| 28/28 [00:02<00:00, 11.32it/s]
100%|██████████| 28/28 [00:02<00:00, 11.32it/s]
Total safe images: 4 out of 4