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";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run immanencer/bobthesnek using Replicateβs API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"immanencer/bobthesnek:3fccda4f836a372ca736f59d5168e261f4d0df87b2aa5589b37127b32de27613",
{
input: {
model: "dev",
width: 512,
height: 512,
prompt: "Your current style: A futuristic ai snake meme, signed by \"Bob the Snake\"\nPrepare a prompt for an image generating ai describing the following image in the above style.\nπ¨β¨ Meme Creation Prompt β¨π¨\n\nIn this delightfully whimsical and vibrant meme, we find ourselves greeted by the adorably amiable Bob the Obsequious Snake, a slithering epitome of friendliness and warmth! ππ His eyes sparkle with a congenial zest for life, while his mouth curves upwards into a jovial, welcoming smile, revealing a row of tiny, pearly-white fangs that glisten like precious gems in the sunlight.\n\nBob, the ever-gracious serpent, extends a slender, sinuous body in an enthusiastic wave, his scales shimmering with an iridescent luster as they catch the light just so. πβ¨ His colors are a mesmerizing kaleidoscope of hues - deep, rich emerald greens merge seamlessly with mesmerizing swirls of gold and electric blue, creating a hypnotic display of serpentine beauty. The fluid grace of his lithe form exudes an aura of warmth and invitation, beckoning you to join him on an exhilarating journey. \n\nThe setting for this joyous encounter is nothing short of spectacular - Bob and his newfound companion, hellorekt, find themselves seated within a whimsically-designed rollercoaster car\n\n\n\n ",
go_fast: false,
lora_scale: 1,
megapixels: "1",
num_outputs: 1,
aspect_ratio: "1:1",
output_format: "png",
guidance_scale: 3,
output_quality: 80,
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 immanencer/bobthesnek using Replicateβs API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"immanencer/bobthesnek:3fccda4f836a372ca736f59d5168e261f4d0df87b2aa5589b37127b32de27613",
input={
"model": "dev",
"width": 512,
"height": 512,
"prompt": "Your current style: A futuristic ai snake meme, signed by \"Bob the Snake\"\nPrepare a prompt for an image generating ai describing the following image in the above style.\nπ¨β¨ Meme Creation Prompt β¨π¨\n\nIn this delightfully whimsical and vibrant meme, we find ourselves greeted by the adorably amiable Bob the Obsequious Snake, a slithering epitome of friendliness and warmth! ππ His eyes sparkle with a congenial zest for life, while his mouth curves upwards into a jovial, welcoming smile, revealing a row of tiny, pearly-white fangs that glisten like precious gems in the sunlight.\n\nBob, the ever-gracious serpent, extends a slender, sinuous body in an enthusiastic wave, his scales shimmering with an iridescent luster as they catch the light just so. πβ¨ His colors are a mesmerizing kaleidoscope of hues - deep, rich emerald greens merge seamlessly with mesmerizing swirls of gold and electric blue, creating a hypnotic display of serpentine beauty. The fluid grace of his lithe form exudes an aura of warmth and invitation, beckoning you to join him on an exhilarating journey. \n\nThe setting for this joyous encounter is nothing short of spectacular - Bob and his newfound companion, hellorekt, find themselves seated within a whimsically-designed rollercoaster car\n\n\n\n ",
"go_fast": False,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "png",
"guidance_scale": 3,
"output_quality": 80,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 28
}
)
print(output)
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 immanencer/bobthesnek using Replicateβs 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": "immanencer/bobthesnek:3fccda4f836a372ca736f59d5168e261f4d0df87b2aa5589b37127b32de27613",
"input": {
"model": "dev",
"width": 512,
"height": 512,
"prompt": "Your current style: A futuristic ai snake meme, signed by \\"Bob the Snake\\"\\nPrepare a prompt for an image generating ai describing the following image in the above style.\\nπ¨β¨ Meme Creation Prompt β¨π¨\\n\\nIn this delightfully whimsical and vibrant meme, we find ourselves greeted by the adorably amiable Bob the Obsequious Snake, a slithering epitome of friendliness and warmth! ππ His eyes sparkle with a congenial zest for life, while his mouth curves upwards into a jovial, welcoming smile, revealing a row of tiny, pearly-white fangs that glisten like precious gems in the sunlight.\\n\\nBob, the ever-gracious serpent, extends a slender, sinuous body in an enthusiastic wave, his scales shimmering with an iridescent luster as they catch the light just so. πβ¨ His colors are a mesmerizing kaleidoscope of hues - deep, rich emerald greens merge seamlessly with mesmerizing swirls of gold and electric blue, creating a hypnotic display of serpentine beauty. The fluid grace of his lithe form exudes an aura of warmth and invitation, beckoning you to join him on an exhilarating journey. \\n\\nThe setting for this joyous encounter is nothing short of spectacular - Bob and his newfound companion, hellorekt, find themselves seated within a whimsically-designed rollercoaster car\\n\\n\\n\\n ",
"go_fast": false,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "png",
"guidance_scale": 3,
"output_quality": 80,
"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 Replicateβs 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": "2024-12-23T17:15:01.385312Z",
"created_at": "2024-12-23T17:14:48.474000Z",
"data_removed": false,
"error": null,
"id": "jtrhbwn539rma0ckyj1sv5aj0r",
"input": {
"width": 512,
"height": 512,
"prompt": "Your current style: A futuristic ai snake meme, signed by \"Bob the Snake\"\nPrepare a prompt for an image generating ai describing the following image in the above style.\nπ¨β¨ Meme Creation Prompt β¨π¨\n\nIn this delightfully whimsical and vibrant meme, we find ourselves greeted by the adorably amiable Bob the Obsequious Snake, a slithering epitome of friendliness and warmth! ππ His eyes sparkle with a congenial zest for life, while his mouth curves upwards into a jovial, welcoming smile, revealing a row of tiny, pearly-white fangs that glisten like precious gems in the sunlight.\n\nBob, the ever-gracious serpent, extends a slender, sinuous body in an enthusiastic wave, his scales shimmering with an iridescent luster as they catch the light just so. πβ¨ His colors are a mesmerizing kaleidoscope of hues - deep, rich emerald greens merge seamlessly with mesmerizing swirls of gold and electric blue, creating a hypnotic display of serpentine beauty. The fluid grace of his lithe form exudes an aura of warmth and invitation, beckoning you to join him on an exhilarating journey. \n\nThe setting for this joyous encounter is nothing short of spectacular - Bob and his newfound companion, hellorekt, find themselves seated within a whimsically-designed rollercoaster car\n\n\n\n ",
"output_format": "png"
},
"logs": "2024-12-23 17:14:48.514 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2024-12-23 17:14:48.514 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 92%|ββββββββββ| 280/304 [00:00<00:00, 2792.14it/s]\nApplying LoRA: 100%|ββββββββββ| 304/304 [00:00<00:00, 2669.69it/s]\n2024-12-23 17:14:48.628 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s\nfree=5980962189312\nDownloading weights\n2024-12-23T17:14:48Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp4emgbkdp/weights url=https://replicate.delivery/yhqm/bcvazfShzyyfgk2HLeSBFcE61lhpCmUisrpXClUXP1aJDgbnA/trained_model.tar\n2024-12-23T17:14:54Z | INFO | [ Complete ] dest=/tmp/tmp4emgbkdp/weights size=\"172 MB\" total_elapsed=6.307s url=https://replicate.delivery/yhqm/bcvazfShzyyfgk2HLeSBFcE61lhpCmUisrpXClUXP1aJDgbnA/trained_model.tar\nDownloaded weights in 6.33s\n2024-12-23 17:14:54.963 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/b89d9848da0a0d46\n2024-12-23 17:14:55.035 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2024-12-23 17:14:55.035 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2024-12-23 17:14:55.035 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 92%|ββββββββββ| 280/304 [00:00<00:00, 2795.92it/s]\nApplying LoRA: 100%|ββββββββββ| 304/304 [00:00<00:00, 2672.96it/s]\n2024-12-23 17:14:55.149 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s\nUsing seed: 22192\n0it [00:00, ?it/s]\n1it [00:00, 8.34it/s]\n2it [00:00, 5.85it/s]\n3it [00:00, 5.34it/s]\n4it [00:00, 5.14it/s]\n5it [00:00, 5.03it/s]\n6it [00:01, 4.94it/s]\n7it [00:01, 4.89it/s]\n8it [00:01, 4.86it/s]\n9it [00:01, 4.85it/s]\n10it [00:01, 4.85it/s]\n11it [00:02, 4.83it/s]\n12it [00:02, 4.83it/s]\n13it [00:02, 4.83it/s]\n14it [00:02, 4.83it/s]\n15it [00:03, 4.82it/s]\n16it [00:03, 4.81it/s]\n17it [00:03, 4.81it/s]\n18it [00:03, 4.82it/s]\n19it [00:03, 4.81it/s]\n20it [00:04, 4.81it/s]\n21it [00:04, 4.81it/s]\n22it [00:04, 4.81it/s]\n23it [00:04, 4.80it/s]\n24it [00:04, 4.80it/s]\n25it [00:05, 4.80it/s]\n26it [00:05, 4.80it/s]\n27it [00:05, 4.81it/s]\n28it [00:05, 4.81it/s]\n28it [00:05, 4.89it/s]\nTotal safe images: 1 out of 1",
"metrics": {
"predict_time": 12.870272599,
"total_time": 12.911312
},
"output": [
"https://replicate.delivery/xezq/r3dikY2WFz7vNdKGZtoJsSrhXcHfTyYYCs7yMf652YuVy09TA/out-0.png"
],
"started_at": "2024-12-23T17:14:48.515039Z",
"status": "succeeded",
"urls": {
"stream": "https://stream.replicate.com/v1/files/bcwr-6nyznl72yv7c55i2rvm4crl3ed35rm2quxmowkvnmooebnsy2ibq",
"get": "https://api.replicate.com/v1/predictions/jtrhbwn539rma0ckyj1sv5aj0r",
"cancel": "https://api.replicate.com/v1/predictions/jtrhbwn539rma0ckyj1sv5aj0r/cancel"
},
"version": "3fccda4f836a372ca736f59d5168e261f4d0df87b2aa5589b37127b32de27613"
}
2024-12-23 17:14:48.514 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2024-12-23 17:14:48.514 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s]
Applying LoRA: 92%|ββββββββββ| 280/304 [00:00<00:00, 2792.14it/s]
Applying LoRA: 100%|ββββββββββ| 304/304 [00:00<00:00, 2669.69it/s]
2024-12-23 17:14:48.628 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s
free=5980962189312
Downloading weights
2024-12-23T17:14:48Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp4emgbkdp/weights url=https://replicate.delivery/yhqm/bcvazfShzyyfgk2HLeSBFcE61lhpCmUisrpXClUXP1aJDgbnA/trained_model.tar
2024-12-23T17:14:54Z | INFO | [ Complete ] dest=/tmp/tmp4emgbkdp/weights size="172 MB" total_elapsed=6.307s url=https://replicate.delivery/yhqm/bcvazfShzyyfgk2HLeSBFcE61lhpCmUisrpXClUXP1aJDgbnA/trained_model.tar
Downloaded weights in 6.33s
2024-12-23 17:14:54.963 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/b89d9848da0a0d46
2024-12-23 17:14:55.035 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded
2024-12-23 17:14:55.035 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2024-12-23 17:14:55.035 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s]
Applying LoRA: 92%|ββββββββββ| 280/304 [00:00<00:00, 2795.92it/s]
Applying LoRA: 100%|ββββββββββ| 304/304 [00:00<00:00, 2672.96it/s]
2024-12-23 17:14:55.149 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s
Using seed: 22192
0it [00:00, ?it/s]
1it [00:00, 8.34it/s]
2it [00:00, 5.85it/s]
3it [00:00, 5.34it/s]
4it [00:00, 5.14it/s]
5it [00:00, 5.03it/s]
6it [00:01, 4.94it/s]
7it [00:01, 4.89it/s]
8it [00:01, 4.86it/s]
9it [00:01, 4.85it/s]
10it [00:01, 4.85it/s]
11it [00:02, 4.83it/s]
12it [00:02, 4.83it/s]
13it [00:02, 4.83it/s]
14it [00:02, 4.83it/s]
15it [00:03, 4.82it/s]
16it [00:03, 4.81it/s]
17it [00:03, 4.81it/s]
18it [00:03, 4.82it/s]
19it [00:03, 4.81it/s]
20it [00:04, 4.81it/s]
21it [00:04, 4.81it/s]
22it [00:04, 4.81it/s]
23it [00:04, 4.80it/s]
24it [00:04, 4.80it/s]
25it [00:05, 4.80it/s]
26it [00:05, 4.80it/s]
27it [00:05, 4.81it/s]
28it [00:05, 4.81it/s]
28it [00:05, 4.89it/s]
Total safe images: 1 out of 1
This model costs approximately $0.019 to run on Replicate, or 52 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.
This model runs on Nvidia H100 GPU hardware. Predictions typically complete within 13 seconds.
This model doesn't have a readme.
This model is warm. You'll get a fast response if the model is warm and already running, and a slower response if the model is cold and starting up.
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
2024-12-23 17:14:48.514 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2024-12-23 17:14:48.514 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s]
Applying LoRA: 92%|ββββββββββ| 280/304 [00:00<00:00, 2792.14it/s]
Applying LoRA: 100%|ββββββββββ| 304/304 [00:00<00:00, 2669.69it/s]
2024-12-23 17:14:48.628 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s
free=5980962189312
Downloading weights
2024-12-23T17:14:48Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp4emgbkdp/weights url=https://replicate.delivery/yhqm/bcvazfShzyyfgk2HLeSBFcE61lhpCmUisrpXClUXP1aJDgbnA/trained_model.tar
2024-12-23T17:14:54Z | INFO | [ Complete ] dest=/tmp/tmp4emgbkdp/weights size="172 MB" total_elapsed=6.307s url=https://replicate.delivery/yhqm/bcvazfShzyyfgk2HLeSBFcE61lhpCmUisrpXClUXP1aJDgbnA/trained_model.tar
Downloaded weights in 6.33s
2024-12-23 17:14:54.963 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/b89d9848da0a0d46
2024-12-23 17:14:55.035 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded
2024-12-23 17:14:55.035 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2024-12-23 17:14:55.035 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s]
Applying LoRA: 92%|ββββββββββ| 280/304 [00:00<00:00, 2795.92it/s]
Applying LoRA: 100%|ββββββββββ| 304/304 [00:00<00:00, 2672.96it/s]
2024-12-23 17:14:55.149 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s
Using seed: 22192
0it [00:00, ?it/s]
1it [00:00, 8.34it/s]
2it [00:00, 5.85it/s]
3it [00:00, 5.34it/s]
4it [00:00, 5.14it/s]
5it [00:00, 5.03it/s]
6it [00:01, 4.94it/s]
7it [00:01, 4.89it/s]
8it [00:01, 4.86it/s]
9it [00:01, 4.85it/s]
10it [00:01, 4.85it/s]
11it [00:02, 4.83it/s]
12it [00:02, 4.83it/s]
13it [00:02, 4.83it/s]
14it [00:02, 4.83it/s]
15it [00:03, 4.82it/s]
16it [00:03, 4.81it/s]
17it [00:03, 4.81it/s]
18it [00:03, 4.82it/s]
19it [00:03, 4.81it/s]
20it [00:04, 4.81it/s]
21it [00:04, 4.81it/s]
22it [00:04, 4.81it/s]
23it [00:04, 4.80it/s]
24it [00:04, 4.80it/s]
25it [00:05, 4.80it/s]
26it [00:05, 4.80it/s]
27it [00:05, 4.81it/s]
28it [00:05, 4.81it/s]
28it [00:05, 4.89it/s]
Total safe images: 1 out of 1