maczzzzzzz / degenpepe
- Public
- 50 runs
-
H100
Prediction
maczzzzzzz/degenpepe:7c2c12af1378077f5a46e51f2b0f175680b56f29c9e59cac3cdb5a6699c9be98ID8jdc7e4pfxrmc0ckg27841zje8StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- in degen style 2d pepe sitting inside a 1999 honda civic
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "in degen style 2d pepe sitting inside a 1999 honda civic", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run maczzzzzzz/degenpepe using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "maczzzzzzz/degenpepe:7c2c12af1378077f5a46e51f2b0f175680b56f29c9e59cac3cdb5a6699c9be98", { input: { model: "dev", prompt: "in degen style 2d pepe sitting inside a 1999 honda civic", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", 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.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun maczzzzzzz/degenpepe using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "maczzzzzzz/degenpepe:7c2c12af1378077f5a46e51f2b0f175680b56f29c9e59cac3cdb5a6699c9be98", input={ "model": "dev", "prompt": "in degen style 2d pepe sitting inside a 1999 honda civic", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "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.
Run maczzzzzzz/degenpepe 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": "maczzzzzzz/degenpepe:7c2c12af1378077f5a46e51f2b0f175680b56f29c9e59cac3cdb5a6699c9be98", "input": { "model": "dev", "prompt": "in degen style 2d pepe sitting inside a 1999 honda civic", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-12-01T04:50:59.467352Z", "created_at": "2024-12-01T04:50:48.575000Z", "data_removed": false, "error": null, "id": "8jdc7e4pfxrmc0ckg27841zje8", "input": { "model": "dev", "prompt": "in degen style 2d pepe sitting inside a 1999 honda civic", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2024-12-01 04:50:48.580 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys\n2024-12-01 04:50:48.580 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 91%|█████████ | 277/304 [00:00<00:00, 2746.38it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2572.95it/s]\n2024-12-01 04:50:48.698 | SUCCESS | fp8.lora_loading:unload_loras:559 - LoRAs unloaded in 0.12s\nfree=29181748097024\nDownloading weights\n2024-12-01T04:50:48Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpzna8988t/weights url=https://replicate.delivery/xezq/r0EQYHMAzJqeaq2Xepi381QHJ6AeUwBQYfoewhXOVQ4199yeE/trained_model.tar\n2024-12-01T04:50:53Z | INFO | [ Complete ] dest=/tmp/tmpzna8988t/weights size=\"172 MB\" total_elapsed=4.322s url=https://replicate.delivery/xezq/r0EQYHMAzJqeaq2Xepi381QHJ6AeUwBQYfoewhXOVQ4199yeE/trained_model.tar\nDownloaded weights in 4.35s\n2024-12-01 04:50:53.047 | INFO | fp8.lora_loading:convert_lora_weights:493 - Loading LoRA weights for /src/weights-cache/963b3ad31a8e5576\n2024-12-01 04:50:53.119 | INFO | fp8.lora_loading:convert_lora_weights:514 - LoRA weights loaded\n2024-12-01 04:50:53.119 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys\n2024-12-01 04:50:53.119 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 91%|█████████ | 277/304 [00:00<00:00, 2749.48it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2575.54it/s]\n2024-12-01 04:50:53.237 | SUCCESS | fp8.lora_loading:load_lora:534 - LoRA applied in 0.19s\nUsing seed: 41526\n0it [00:00, ?it/s]\n1it [00:00, 8.29it/s]\n2it [00:00, 5.80it/s]\n3it [00:00, 5.30it/s]\n4it [00:00, 5.08it/s]\n5it [00:00, 4.96it/s]\n6it [00:01, 4.87it/s]\n7it [00:01, 4.83it/s]\n8it [00:01, 4.81it/s]\n9it [00:01, 4.80it/s]\n10it [00:02, 4.78it/s]\n11it [00:02, 4.77it/s]\n12it [00:02, 4.76it/s]\n13it [00:02, 4.75it/s]\n14it [00:02, 4.75it/s]\n15it [00:03, 4.75it/s]\n16it [00:03, 4.75it/s]\n17it [00:03, 4.74it/s]\n18it [00:03, 4.74it/s]\n19it [00:03, 4.74it/s]\n20it [00:04, 4.74it/s]\n21it [00:04, 4.74it/s]\n22it [00:04, 4.73it/s]\n23it [00:04, 4.74it/s]\n24it [00:04, 4.74it/s]\n25it [00:05, 4.75it/s]\n26it [00:05, 4.75it/s]\n27it [00:05, 4.75it/s]\n28it [00:05, 4.75it/s]\n28it [00:05, 4.82it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 10.885502411000001, "total_time": 10.892352 }, "output": [ "https://replicate.delivery/xezq/z3CfaBTcvkQPZSwK0eLWUO7kINeB5FQifiHk9Mvi0vANTnZPB/out-0.webp" ], "started_at": "2024-12-01T04:50:48.581850Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-4untl53sxfmeqqpbrd7rswcfmsdxcnoxyy2lwlupeszwnhv6uwja", "get": "https://api.replicate.com/v1/predictions/8jdc7e4pfxrmc0ckg27841zje8", "cancel": "https://api.replicate.com/v1/predictions/8jdc7e4pfxrmc0ckg27841zje8/cancel" }, "version": "7c2c12af1378077f5a46e51f2b0f175680b56f29c9e59cac3cdb5a6699c9be98" }Generated in2024-12-01 04:50:48.580 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys 2024-12-01 04:50:48.580 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 91%|█████████ | 277/304 [00:00<00:00, 2746.38it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2572.95it/s] 2024-12-01 04:50:48.698 | SUCCESS | fp8.lora_loading:unload_loras:559 - LoRAs unloaded in 0.12s free=29181748097024 Downloading weights 2024-12-01T04:50:48Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpzna8988t/weights url=https://replicate.delivery/xezq/r0EQYHMAzJqeaq2Xepi381QHJ6AeUwBQYfoewhXOVQ4199yeE/trained_model.tar 2024-12-01T04:50:53Z | INFO | [ Complete ] dest=/tmp/tmpzna8988t/weights size="172 MB" total_elapsed=4.322s url=https://replicate.delivery/xezq/r0EQYHMAzJqeaq2Xepi381QHJ6AeUwBQYfoewhXOVQ4199yeE/trained_model.tar Downloaded weights in 4.35s 2024-12-01 04:50:53.047 | INFO | fp8.lora_loading:convert_lora_weights:493 - Loading LoRA weights for /src/weights-cache/963b3ad31a8e5576 2024-12-01 04:50:53.119 | INFO | fp8.lora_loading:convert_lora_weights:514 - LoRA weights loaded 2024-12-01 04:50:53.119 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys 2024-12-01 04:50:53.119 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 91%|█████████ | 277/304 [00:00<00:00, 2749.48it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2575.54it/s] 2024-12-01 04:50:53.237 | SUCCESS | fp8.lora_loading:load_lora:534 - LoRA applied in 0.19s Using seed: 41526 0it [00:00, ?it/s] 1it [00:00, 8.29it/s] 2it [00:00, 5.80it/s] 3it [00:00, 5.30it/s] 4it [00:00, 5.08it/s] 5it [00:00, 4.96it/s] 6it [00:01, 4.87it/s] 7it [00:01, 4.83it/s] 8it [00:01, 4.81it/s] 9it [00:01, 4.80it/s] 10it [00:02, 4.78it/s] 11it [00:02, 4.77it/s] 12it [00:02, 4.76it/s] 13it [00:02, 4.75it/s] 14it [00:02, 4.75it/s] 15it [00:03, 4.75it/s] 16it [00:03, 4.75it/s] 17it [00:03, 4.74it/s] 18it [00:03, 4.74it/s] 19it [00:03, 4.74it/s] 20it [00:04, 4.74it/s] 21it [00:04, 4.74it/s] 22it [00:04, 4.73it/s] 23it [00:04, 4.74it/s] 24it [00:04, 4.74it/s] 25it [00:05, 4.75it/s] 26it [00:05, 4.75it/s] 27it [00:05, 4.75it/s] 28it [00:05, 4.75it/s] 28it [00:05, 4.82it/s] Total safe images: 1 out of 1Prediction
maczzzzzzz/degenpepe:7c2c12af1378077f5a46e51f2b0f175680b56f29c9e59cac3cdb5a6699c9be98IDsp6zb4x3z9rmc0ckg28btrny6rStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- in degen style 2d pepe smoking a cigar beside a beautiful woman
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "in degen style 2d pepe smoking a cigar beside a beautiful woman ", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run maczzzzzzz/degenpepe using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "maczzzzzzz/degenpepe:7c2c12af1378077f5a46e51f2b0f175680b56f29c9e59cac3cdb5a6699c9be98", { input: { model: "dev", prompt: "in degen style 2d pepe smoking a cigar beside a beautiful woman ", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", 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.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun maczzzzzzz/degenpepe using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "maczzzzzzz/degenpepe:7c2c12af1378077f5a46e51f2b0f175680b56f29c9e59cac3cdb5a6699c9be98", input={ "model": "dev", "prompt": "in degen style 2d pepe smoking a cigar beside a beautiful woman ", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "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.
Run maczzzzzzz/degenpepe 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": "maczzzzzzz/degenpepe:7c2c12af1378077f5a46e51f2b0f175680b56f29c9e59cac3cdb5a6699c9be98", "input": { "model": "dev", "prompt": "in degen style 2d pepe smoking a cigar beside a beautiful woman ", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-12-01T04:53:12.523138Z", "created_at": "2024-12-01T04:53:03.098000Z", "data_removed": false, "error": null, "id": "sp6zb4x3z9rmc0ckg28btrny6r", "input": { "model": "dev", "prompt": "in degen style 2d pepe smoking a cigar beside a beautiful woman ", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2024-12-01 04:53:06.019 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys\n2024-12-01 04:53:06.019 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 91%|█████████ | 277/304 [00:00<00:00, 2745.99it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2572.98it/s]\n2024-12-01 04:53:06.137 | SUCCESS | fp8.lora_loading:unload_loras:559 - LoRAs unloaded in 0.12s\n2024-12-01 04:53:06.139 | INFO | fp8.lora_loading:convert_lora_weights:493 - Loading LoRA weights for /src/weights-cache/963b3ad31a8e5576\n2024-12-01 04:53:06.250 | INFO | fp8.lora_loading:convert_lora_weights:514 - LoRA weights loaded\n2024-12-01 04:53:06.250 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys\n2024-12-01 04:53:06.250 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 91%|█████████ | 277/304 [00:00<00:00, 2750.73it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2576.62it/s]\n2024-12-01 04:53:06.368 | SUCCESS | fp8.lora_loading:load_lora:534 - LoRA applied in 0.23s\nUsing seed: 9800\n0it [00:00, ?it/s]\n1it [00:00, 8.33it/s]\n2it [00:00, 5.80it/s]\n3it [00:00, 5.29it/s]\n4it [00:00, 5.07it/s]\n5it [00:00, 4.94it/s]\n6it [00:01, 4.85it/s]\n7it [00:01, 4.83it/s]\n8it [00:01, 4.81it/s]\n9it [00:01, 4.80it/s]\n10it [00:02, 4.79it/s]\n11it [00:02, 4.77it/s]\n12it [00:02, 4.77it/s]\n13it [00:02, 4.77it/s]\n14it [00:02, 4.77it/s]\n15it [00:03, 4.76it/s]\n16it [00:03, 4.75it/s]\n17it [00:03, 4.75it/s]\n18it [00:03, 4.75it/s]\n19it [00:03, 4.75it/s]\n20it [00:04, 4.75it/s]\n21it [00:04, 4.74it/s]\n22it [00:04, 4.74it/s]\n23it [00:04, 4.75it/s]\n24it [00:04, 4.74it/s]\n25it [00:05, 4.75it/s]\n26it [00:05, 4.75it/s]\n27it [00:05, 4.75it/s]\n28it [00:05, 4.75it/s]\n28it [00:05, 4.83it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 6.503177573, "total_time": 9.425138 }, "output": [ "https://replicate.delivery/xezq/IOC2LKK6zJ5vFBxcZKA9u7wpWQImk3tXILlM6CwVuFOudm9E/out-0.webp" ], "started_at": "2024-12-01T04:53:06.019960Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-lrponrdcr3x5sbmfi3mjmrczkzmxnawf4shj7it5e75a46fz4pzq", "get": "https://api.replicate.com/v1/predictions/sp6zb4x3z9rmc0ckg28btrny6r", "cancel": "https://api.replicate.com/v1/predictions/sp6zb4x3z9rmc0ckg28btrny6r/cancel" }, "version": "7c2c12af1378077f5a46e51f2b0f175680b56f29c9e59cac3cdb5a6699c9be98" }Generated in2024-12-01 04:53:06.019 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys 2024-12-01 04:53:06.019 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 91%|█████████ | 277/304 [00:00<00:00, 2745.99it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2572.98it/s] 2024-12-01 04:53:06.137 | SUCCESS | fp8.lora_loading:unload_loras:559 - LoRAs unloaded in 0.12s 2024-12-01 04:53:06.139 | INFO | fp8.lora_loading:convert_lora_weights:493 - Loading LoRA weights for /src/weights-cache/963b3ad31a8e5576 2024-12-01 04:53:06.250 | INFO | fp8.lora_loading:convert_lora_weights:514 - LoRA weights loaded 2024-12-01 04:53:06.250 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys 2024-12-01 04:53:06.250 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 91%|█████████ | 277/304 [00:00<00:00, 2750.73it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2576.62it/s] 2024-12-01 04:53:06.368 | SUCCESS | fp8.lora_loading:load_lora:534 - LoRA applied in 0.23s Using seed: 9800 0it [00:00, ?it/s] 1it [00:00, 8.33it/s] 2it [00:00, 5.80it/s] 3it [00:00, 5.29it/s] 4it [00:00, 5.07it/s] 5it [00:00, 4.94it/s] 6it [00:01, 4.85it/s] 7it [00:01, 4.83it/s] 8it [00:01, 4.81it/s] 9it [00:01, 4.80it/s] 10it [00:02, 4.79it/s] 11it [00:02, 4.77it/s] 12it [00:02, 4.77it/s] 13it [00:02, 4.77it/s] 14it [00:02, 4.77it/s] 15it [00:03, 4.76it/s] 16it [00:03, 4.75it/s] 17it [00:03, 4.75it/s] 18it [00:03, 4.75it/s] 19it [00:03, 4.75it/s] 20it [00:04, 4.75it/s] 21it [00:04, 4.74it/s] 22it [00:04, 4.74it/s] 23it [00:04, 4.75it/s] 24it [00:04, 4.74it/s] 25it [00:05, 4.75it/s] 26it [00:05, 4.75it/s] 27it [00:05, 4.75it/s] 28it [00:05, 4.75it/s] 28it [00:05, 4.83it/s] Total safe images: 1 out of 1Prediction
maczzzzzzz/degenpepe:7c2c12af1378077f5a46e51f2b0f175680b56f29c9e59cac3cdb5a6699c9be98IDwwc1d1x6p1rmc0ckg28ttpcj90StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- seed
- 69
- model
- dev
- prompt
- in degen style 2d pepe sitting inside a 1999 honda civic
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "seed": 69, "model": "dev", "prompt": "in degen style 2d pepe sitting inside a 1999 honda civic ", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run maczzzzzzz/degenpepe using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "maczzzzzzz/degenpepe:7c2c12af1378077f5a46e51f2b0f175680b56f29c9e59cac3cdb5a6699c9be98", { input: { seed: 69, model: "dev", prompt: "in degen style 2d pepe sitting inside a 1999 honda civic ", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", 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.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun maczzzzzzz/degenpepe using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "maczzzzzzz/degenpepe:7c2c12af1378077f5a46e51f2b0f175680b56f29c9e59cac3cdb5a6699c9be98", input={ "seed": 69, "model": "dev", "prompt": "in degen style 2d pepe sitting inside a 1999 honda civic ", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "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.
Run maczzzzzzz/degenpepe 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": "maczzzzzzz/degenpepe:7c2c12af1378077f5a46e51f2b0f175680b56f29c9e59cac3cdb5a6699c9be98", "input": { "seed": 69, "model": "dev", "prompt": "in degen style 2d pepe sitting inside a 1999 honda civic ", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-12-01T04:54:18.955064Z", "created_at": "2024-12-01T04:54:09.328000Z", "data_removed": false, "error": null, "id": "wwc1d1x6p1rmc0ckg28ttpcj90", "input": { "seed": 69, "model": "dev", "prompt": "in degen style 2d pepe sitting inside a 1999 honda civic ", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2024-12-01 04:54:09.902 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys\n2024-12-01 04:54:09.902 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 91%|█████████ | 276/304 [00:00<00:00, 2747.81it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2663.22it/s]\n2024-12-01 04:54:10.017 | SUCCESS | fp8.lora_loading:unload_loras:559 - LoRAs unloaded in 0.11s\nfree=29127184498688\nDownloading weights\n2024-12-01T04:54:10Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp3zo4soa1/weights url=https://replicate.delivery/xezq/r0EQYHMAzJqeaq2Xepi381QHJ6AeUwBQYfoewhXOVQ4199yeE/trained_model.tar\n2024-12-01T04:54:12Z | INFO | [ Complete ] dest=/tmp/tmp3zo4soa1/weights size=\"172 MB\" total_elapsed=2.576s url=https://replicate.delivery/xezq/r0EQYHMAzJqeaq2Xepi381QHJ6AeUwBQYfoewhXOVQ4199yeE/trained_model.tar\nDownloaded weights in 2.60s\n2024-12-01 04:54:12.620 | INFO | fp8.lora_loading:convert_lora_weights:493 - Loading LoRA weights for /src/weights-cache/963b3ad31a8e5576\n2024-12-01 04:54:12.693 | INFO | fp8.lora_loading:convert_lora_weights:514 - LoRA weights loaded\n2024-12-01 04:54:12.693 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys\n2024-12-01 04:54:12.693 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 91%|█████████ | 276/304 [00:00<00:00, 2754.39it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2668.88it/s]\n2024-12-01 04:54:12.807 | SUCCESS | fp8.lora_loading:load_lora:534 - LoRA applied in 0.19s\nUsing seed: 69\n0it [00:00, ?it/s]\n1it [00:00, 8.33it/s]\n2it [00:00, 5.84it/s]\n3it [00:00, 5.34it/s]\n4it [00:00, 5.13it/s]\n5it [00:00, 5.02it/s]\n6it [00:01, 4.95it/s]\n7it [00:01, 4.91it/s]\n8it [00:01, 4.89it/s]\n9it [00:01, 4.87it/s]\n10it [00:01, 4.85it/s]\n11it [00:02, 4.85it/s]\n12it [00:02, 4.84it/s]\n13it [00:02, 4.84it/s]\n14it [00:02, 4.84it/s]\n15it [00:03, 4.84it/s]\n16it [00:03, 4.83it/s]\n17it [00:03, 4.83it/s]\n18it [00:03, 4.83it/s]\n19it [00:03, 4.83it/s]\n20it [00:04, 4.83it/s]\n21it [00:04, 4.83it/s]\n22it [00:04, 4.83it/s]\n23it [00:04, 4.83it/s]\n24it [00:04, 4.83it/s]\n25it [00:05, 4.83it/s]\n26it [00:05, 4.83it/s]\n27it [00:05, 4.83it/s]\n28it [00:05, 4.83it/s]\n28it [00:05, 4.90it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 9.052015492, "total_time": 9.627064 }, "output": [ "https://replicate.delivery/xezq/6NAqoS4itRY5Ol18IkTP9O4Q8rOTOg6nsWJDHWRmVvue7M7JA/out-0.webp" ], "started_at": "2024-12-01T04:54:09.903049Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-auyk2xua4ovvpp2ocoscesasn43ts2xrmkeg7jva75dojd6gt77a", "get": "https://api.replicate.com/v1/predictions/wwc1d1x6p1rmc0ckg28ttpcj90", "cancel": "https://api.replicate.com/v1/predictions/wwc1d1x6p1rmc0ckg28ttpcj90/cancel" }, "version": "7c2c12af1378077f5a46e51f2b0f175680b56f29c9e59cac3cdb5a6699c9be98" }Generated in2024-12-01 04:54:09.902 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys 2024-12-01 04:54:09.902 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 91%|█████████ | 276/304 [00:00<00:00, 2747.81it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2663.22it/s] 2024-12-01 04:54:10.017 | SUCCESS | fp8.lora_loading:unload_loras:559 - LoRAs unloaded in 0.11s free=29127184498688 Downloading weights 2024-12-01T04:54:10Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp3zo4soa1/weights url=https://replicate.delivery/xezq/r0EQYHMAzJqeaq2Xepi381QHJ6AeUwBQYfoewhXOVQ4199yeE/trained_model.tar 2024-12-01T04:54:12Z | INFO | [ Complete ] dest=/tmp/tmp3zo4soa1/weights size="172 MB" total_elapsed=2.576s url=https://replicate.delivery/xezq/r0EQYHMAzJqeaq2Xepi381QHJ6AeUwBQYfoewhXOVQ4199yeE/trained_model.tar Downloaded weights in 2.60s 2024-12-01 04:54:12.620 | INFO | fp8.lora_loading:convert_lora_weights:493 - Loading LoRA weights for /src/weights-cache/963b3ad31a8e5576 2024-12-01 04:54:12.693 | INFO | fp8.lora_loading:convert_lora_weights:514 - LoRA weights loaded 2024-12-01 04:54:12.693 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys 2024-12-01 04:54:12.693 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 91%|█████████ | 276/304 [00:00<00:00, 2754.39it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2668.88it/s] 2024-12-01 04:54:12.807 | SUCCESS | fp8.lora_loading:load_lora:534 - LoRA applied in 0.19s Using seed: 69 0it [00:00, ?it/s] 1it [00:00, 8.33it/s] 2it [00:00, 5.84it/s] 3it [00:00, 5.34it/s] 4it [00:00, 5.13it/s] 5it [00:00, 5.02it/s] 6it [00:01, 4.95it/s] 7it [00:01, 4.91it/s] 8it [00:01, 4.89it/s] 9it [00:01, 4.87it/s] 10it [00:01, 4.85it/s] 11it [00:02, 4.85it/s] 12it [00:02, 4.84it/s] 13it [00:02, 4.84it/s] 14it [00:02, 4.84it/s] 15it [00:03, 4.84it/s] 16it [00:03, 4.83it/s] 17it [00:03, 4.83it/s] 18it [00:03, 4.83it/s] 19it [00:03, 4.83it/s] 20it [00:04, 4.83it/s] 21it [00:04, 4.83it/s] 22it [00:04, 4.83it/s] 23it [00:04, 4.83it/s] 24it [00:04, 4.83it/s] 25it [00:05, 4.83it/s] 26it [00:05, 4.83it/s] 27it [00:05, 4.83it/s] 28it [00:05, 4.83it/s] 28it [00:05, 4.90it/s] Total safe images: 1 out of 1
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