fofr
/
flux-90s-power-rangers
Flux lora, use "POWER_RANGERS" to trigger image generation
- Public
- 194 runs
-
H100
Prediction
fofr/flux-90s-power-rangers:7088542bIDh10810eqr9rm20cj51yr39c9srStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a low resolution vhs still from 90s POWER_RANGERS showing a giant robot
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a low resolution vhs still from 90s POWER_RANGERS showing a giant robot", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/flux-90s-power-rangers using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-90s-power-rangers:7088542b2b9917d09591dcc8062b60b42fd97f8e0d6cd2a53811bf911d7820fb", { input: { model: "dev", prompt: "a low resolution vhs still from 90s POWER_RANGERS showing a giant robot", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun fofr/flux-90s-power-rangers using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-90s-power-rangers:7088542b2b9917d09591dcc8062b60b42fd97f8e0d6cd2a53811bf911d7820fb", input={ "model": "dev", "prompt": "a low resolution vhs still from 90s POWER_RANGERS showing a giant robot", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "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.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run fofr/flux-90s-power-rangers 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": "7088542b2b9917d09591dcc8062b60b42fd97f8e0d6cd2a53811bf911d7820fb", "input": { "model": "dev", "prompt": "a low resolution vhs still from 90s POWER_RANGERS showing a giant robot", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "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": "2024-09-25T09:23:43.874509Z", "created_at": "2024-09-25T09:23:08.866000Z", "data_removed": false, "error": null, "id": "h10810eqr9rm20cj51yr39c9sr", "input": { "model": "dev", "prompt": "a low resolution vhs still from 90s POWER_RANGERS showing a giant robot", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 23124\nPrompt: a low resolution vhs still from 90s POWER_RANGERS showing a giant robot\n[!] txt2img mode\nUsing dev model\nfree=7196149198848\nDownloading weights\n2024-09-25T09:23:24Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpzp07r9zl/weights url=https://replicate.delivery/yhqm/EHj9imLybZ5JKBW3j89wd2Au641me8hYirfKAGnLNxYQZ4fmA/trained_model.tar\n2024-09-25T09:23:27Z | INFO | [ Complete ] dest=/tmp/tmpzp07r9zl/weights size=\"172 MB\" total_elapsed=2.869s url=https://replicate.delivery/yhqm/EHj9imLybZ5JKBW3j89wd2Au641me8hYirfKAGnLNxYQZ4fmA/trained_model.tar\nDownloaded weights in 2.91s\nLoaded LoRAs in 11.16s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.53it/s]\n 7%|▋ | 2/28 [00:00<00:06, 3.99it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.77it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.67it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.62it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.59it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.56it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.55it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.55it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.54it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.54it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.54it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.53it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.53it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.53it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.53it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.53it/s]\n 64%|██████▍ | 18/28 [00:05<00:02, 3.53it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.53it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.53it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.53it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.53it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.53it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.53it/s]\n 89%|████████▉ | 25/28 [00:07<00:00, 3.53it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.52it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.52it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.52it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.55it/s]", "metrics": { "predict_time": 19.550990005, "total_time": 35.008509 }, "output": [ "https://replicate.delivery/yhqm/c7ATyIhs7LpXLduoEn1UBzIS4CxCfjVFFutVei3PsnrfExAnA/out-0.webp" ], "started_at": "2024-09-25T09:23:24.323519Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/h10810eqr9rm20cj51yr39c9sr", "cancel": "https://api.replicate.com/v1/predictions/h10810eqr9rm20cj51yr39c9sr/cancel" }, "version": "7088542b2b9917d09591dcc8062b60b42fd97f8e0d6cd2a53811bf911d7820fb" }Generated inUsing seed: 23124 Prompt: a low resolution vhs still from 90s POWER_RANGERS showing a giant robot [!] txt2img mode Using dev model free=7196149198848 Downloading weights 2024-09-25T09:23:24Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpzp07r9zl/weights url=https://replicate.delivery/yhqm/EHj9imLybZ5JKBW3j89wd2Au641me8hYirfKAGnLNxYQZ4fmA/trained_model.tar 2024-09-25T09:23:27Z | INFO | [ Complete ] dest=/tmp/tmpzp07r9zl/weights size="172 MB" total_elapsed=2.869s url=https://replicate.delivery/yhqm/EHj9imLybZ5JKBW3j89wd2Au641me8hYirfKAGnLNxYQZ4fmA/trained_model.tar Downloaded weights in 2.91s Loaded LoRAs in 11.16s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.53it/s] 7%|▋ | 2/28 [00:00<00:06, 3.99it/s] 11%|█ | 3/28 [00:00<00:06, 3.77it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.67it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.62it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.59it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.56it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.55it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.55it/s] 36%|███▌ | 10/28 [00:02<00:05, 3.54it/s] 39%|███▉ | 11/28 [00:03<00:04, 3.54it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.54it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.53it/s] 50%|█████ | 14/28 [00:03<00:03, 3.53it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.53it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.53it/s] 61%|██████ | 17/28 [00:04<00:03, 3.53it/s] 64%|██████▍ | 18/28 [00:05<00:02, 3.53it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.53it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.53it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.53it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.53it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.53it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.53it/s] 89%|████████▉ | 25/28 [00:07<00:00, 3.53it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.52it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.52it/s] 100%|██████████| 28/28 [00:07<00:00, 3.52it/s] 100%|██████████| 28/28 [00:07<00:00, 3.55it/s]Prediction
fofr/flux-90s-power-rangers:7088542bIDdtf7sbgzmxrm00cj53ks59y8crStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a low resolution vhs still from 90s POWER_RANGERS showing a weird alien
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a low resolution vhs still from 90s POWER_RANGERS showing a weird alien", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/flux-90s-power-rangers using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-90s-power-rangers:7088542b2b9917d09591dcc8062b60b42fd97f8e0d6cd2a53811bf911d7820fb", { input: { model: "dev", prompt: "a low resolution vhs still from 90s POWER_RANGERS showing a weird alien", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun fofr/flux-90s-power-rangers using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-90s-power-rangers:7088542b2b9917d09591dcc8062b60b42fd97f8e0d6cd2a53811bf911d7820fb", input={ "model": "dev", "prompt": "a low resolution vhs still from 90s POWER_RANGERS showing a weird alien", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "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.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run fofr/flux-90s-power-rangers 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": "7088542b2b9917d09591dcc8062b60b42fd97f8e0d6cd2a53811bf911d7820fb", "input": { "model": "dev", "prompt": "a low resolution vhs still from 90s POWER_RANGERS showing a weird alien", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "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": "2024-09-25T11:18:24.038594Z", "created_at": "2024-09-25T11:18:08.551000Z", "data_removed": false, "error": null, "id": "dtf7sbgzmxrm00cj53ks59y8cr", "input": { "model": "dev", "prompt": "a low resolution vhs still from 90s POWER_RANGERS showing a weird alien", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 52050\nPrompt: a low resolution vhs still from 90s POWER_RANGERS showing a weird alien\n[!] txt2img mode\nUsing dev model\nLoaded LoRAs in 7.09s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.54it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.00it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.78it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.68it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.62it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.59it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.57it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.56it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.55it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.55it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.54it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.54it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.54it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.54it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.54it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.54it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.54it/s]\n 64%|██████▍ | 18/28 [00:05<00:02, 3.54it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.53it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.53it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.54it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.53it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.53it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.53it/s]\n 89%|████████▉ | 25/28 [00:07<00:00, 3.53it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.53it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.54it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.54it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.56it/s]", "metrics": { "predict_time": 15.479917562, "total_time": 15.487594 }, "output": [ "https://replicate.delivery/yhqm/BvUMMN6eeOuneofZzUW9wvCyOpDZDdg9OZGoWc8otCfffGNwJA/out-0.webp" ], "started_at": "2024-09-25T11:18:08.558676Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/dtf7sbgzmxrm00cj53ks59y8cr", "cancel": "https://api.replicate.com/v1/predictions/dtf7sbgzmxrm00cj53ks59y8cr/cancel" }, "version": "7088542b2b9917d09591dcc8062b60b42fd97f8e0d6cd2a53811bf911d7820fb" }Generated inUsing seed: 52050 Prompt: a low resolution vhs still from 90s POWER_RANGERS showing a weird alien [!] txt2img mode Using dev model Loaded LoRAs in 7.09s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.54it/s] 7%|▋ | 2/28 [00:00<00:06, 4.00it/s] 11%|█ | 3/28 [00:00<00:06, 3.78it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.68it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.62it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.59it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.57it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.56it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.55it/s] 36%|███▌ | 10/28 [00:02<00:05, 3.55it/s] 39%|███▉ | 11/28 [00:03<00:04, 3.54it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.54it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.54it/s] 50%|█████ | 14/28 [00:03<00:03, 3.54it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.54it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.54it/s] 61%|██████ | 17/28 [00:04<00:03, 3.54it/s] 64%|██████▍ | 18/28 [00:05<00:02, 3.54it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.53it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.53it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.54it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.53it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.53it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.53it/s] 89%|████████▉ | 25/28 [00:07<00:00, 3.53it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.53it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.54it/s] 100%|██████████| 28/28 [00:07<00:00, 3.54it/s] 100%|██████████| 28/28 [00:07<00:00, 3.56it/s]Prediction
fofr/flux-90s-power-rangers:7088542bIDpjqsezkqjnrm00cj53mvbmp64rStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a low resolution vhs still from 90s POWER_RANGERS showing a weird alien with super powers and sparks
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 3:2
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a low resolution vhs still from 90s POWER_RANGERS showing a weird alien with super powers and sparks", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/flux-90s-power-rangers using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-90s-power-rangers:7088542b2b9917d09591dcc8062b60b42fd97f8e0d6cd2a53811bf911d7820fb", { input: { model: "dev", prompt: "a low resolution vhs still from 90s POWER_RANGERS showing a weird alien with super powers and sparks", lora_scale: 1, num_outputs: 1, aspect_ratio: "3:2", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun fofr/flux-90s-power-rangers using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-90s-power-rangers:7088542b2b9917d09591dcc8062b60b42fd97f8e0d6cd2a53811bf911d7820fb", input={ "model": "dev", "prompt": "a low resolution vhs still from 90s POWER_RANGERS showing a weird alien with super powers and sparks", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "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.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run fofr/flux-90s-power-rangers 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": "7088542b2b9917d09591dcc8062b60b42fd97f8e0d6cd2a53811bf911d7820fb", "input": { "model": "dev", "prompt": "a low resolution vhs still from 90s POWER_RANGERS showing a weird alien with super powers and sparks", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "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": "2024-09-25T11:21:10.443557Z", "created_at": "2024-09-25T11:20:42.133000Z", "data_removed": false, "error": null, "id": "pjqsezkqjnrm00cj53mvbmp64r", "input": { "model": "dev", "prompt": "a low resolution vhs still from 90s POWER_RANGERS showing a weird alien with super powers and sparks", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 19820\nPrompt: a low resolution vhs still from 90s POWER_RANGERS showing a weird alien with super powers and sparks\n[!] txt2img mode\nUsing dev model\nLoaded LoRAs in 9.12s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.63it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.11it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.88it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.78it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.72it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.69it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.67it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.66it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.65it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.65it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.64it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.64it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.64it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.64it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.64it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.64it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.64it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.64it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.64it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.63it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.63it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.64it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.63it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.63it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.63it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.63it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.63it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.63it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.66it/s]", "metrics": { "predict_time": 17.319894313, "total_time": 28.310557 }, "output": [ "https://replicate.delivery/yhqm/WMxWrJZXwy4SLNVAui1f7rUelgaI7NV2ftQYSxzvbfoZCpBOB/out-0.webp" ], "started_at": "2024-09-25T11:20:53.123663Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/pjqsezkqjnrm00cj53mvbmp64r", "cancel": "https://api.replicate.com/v1/predictions/pjqsezkqjnrm00cj53mvbmp64r/cancel" }, "version": "7088542b2b9917d09591dcc8062b60b42fd97f8e0d6cd2a53811bf911d7820fb" }Generated inUsing seed: 19820 Prompt: a low resolution vhs still from 90s POWER_RANGERS showing a weird alien with super powers and sparks [!] txt2img mode Using dev model Loaded LoRAs in 9.12s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.63it/s] 7%|▋ | 2/28 [00:00<00:06, 4.11it/s] 11%|█ | 3/28 [00:00<00:06, 3.88it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.78it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.72it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.69it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.67it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.66it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.65it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.65it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.64it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.64it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.64it/s] 50%|█████ | 14/28 [00:03<00:03, 3.64it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.64it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.64it/s] 61%|██████ | 17/28 [00:04<00:03, 3.64it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.64it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.64it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.63it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.63it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.64it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.63it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.63it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.63it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.63it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.63it/s] 100%|██████████| 28/28 [00:07<00:00, 3.63it/s] 100%|██████████| 28/28 [00:07<00:00, 3.66it/s]Prediction
fofr/flux-90s-power-rangers:7088542bIDmnv8d7kygnrm60cj53n8s04dw8StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a low resolution vhs still from 90s POWER_RANGERS showing a red power ranger sitting in economy on a plane
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 3:2
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a low resolution vhs still from 90s POWER_RANGERS showing a red power ranger sitting in economy on a plane", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/flux-90s-power-rangers using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-90s-power-rangers:7088542b2b9917d09591dcc8062b60b42fd97f8e0d6cd2a53811bf911d7820fb", { input: { model: "dev", prompt: "a low resolution vhs still from 90s POWER_RANGERS showing a red power ranger sitting in economy on a plane", lora_scale: 1, num_outputs: 1, aspect_ratio: "3:2", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun fofr/flux-90s-power-rangers using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-90s-power-rangers:7088542b2b9917d09591dcc8062b60b42fd97f8e0d6cd2a53811bf911d7820fb", input={ "model": "dev", "prompt": "a low resolution vhs still from 90s POWER_RANGERS showing a red power ranger sitting in economy on a plane", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "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.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run fofr/flux-90s-power-rangers 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": "7088542b2b9917d09591dcc8062b60b42fd97f8e0d6cd2a53811bf911d7820fb", "input": { "model": "dev", "prompt": "a low resolution vhs still from 90s POWER_RANGERS showing a red power ranger sitting in economy on a plane", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "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": "2024-09-25T11:22:07.391258Z", "created_at": "2024-09-25T11:21:49.445000Z", "data_removed": false, "error": null, "id": "mnv8d7kygnrm60cj53n8s04dw8", "input": { "model": "dev", "prompt": "a low resolution vhs still from 90s POWER_RANGERS showing a red power ranger sitting in economy on a plane", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 15913\nPrompt: a low resolution vhs still from 90s POWER_RANGERS showing a red power ranger sitting in economy on a plane\n[!] txt2img mode\nUsing dev model\nfree=7028998770688\nDownloading weights\n2024-09-25T11:21:49Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp_d2g21te/weights url=https://replicate.delivery/yhqm/EHj9imLybZ5JKBW3j89wd2Au641me8hYirfKAGnLNxYQZ4fmA/trained_model.tar\n2024-09-25T11:21:50Z | INFO | [ Complete ] dest=/tmp/tmp_d2g21te/weights size=\"172 MB\" total_elapsed=1.329s url=https://replicate.delivery/yhqm/EHj9imLybZ5JKBW3j89wd2Au641me8hYirfKAGnLNxYQZ4fmA/trained_model.tar\nDownloaded weights in 1.36s\nLoaded LoRAs in 9.71s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.61it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.08it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.85it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.76it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.70it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.67it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.65it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.63it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.63it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.62it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.62it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.62it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.61it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.61it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.61it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.61it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.61it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.61it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.61it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.61it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.61it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.61it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.61it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.61it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.61it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.61it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.61it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.61it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.63it/s]", "metrics": { "predict_time": 17.935053168, "total_time": 17.946258 }, "output": [ "https://replicate.delivery/yhqm/9DzTLMdwUao1BF1gED3RZ8PRGmcZcLYZg100BWly7o0XkG4E/out-0.webp" ], "started_at": "2024-09-25T11:21:49.456205Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/mnv8d7kygnrm60cj53n8s04dw8", "cancel": "https://api.replicate.com/v1/predictions/mnv8d7kygnrm60cj53n8s04dw8/cancel" }, "version": "7088542b2b9917d09591dcc8062b60b42fd97f8e0d6cd2a53811bf911d7820fb" }Generated inUsing seed: 15913 Prompt: a low resolution vhs still from 90s POWER_RANGERS showing a red power ranger sitting in economy on a plane [!] txt2img mode Using dev model free=7028998770688 Downloading weights 2024-09-25T11:21:49Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp_d2g21te/weights url=https://replicate.delivery/yhqm/EHj9imLybZ5JKBW3j89wd2Au641me8hYirfKAGnLNxYQZ4fmA/trained_model.tar 2024-09-25T11:21:50Z | INFO | [ Complete ] dest=/tmp/tmp_d2g21te/weights size="172 MB" total_elapsed=1.329s url=https://replicate.delivery/yhqm/EHj9imLybZ5JKBW3j89wd2Au641me8hYirfKAGnLNxYQZ4fmA/trained_model.tar Downloaded weights in 1.36s Loaded LoRAs in 9.71s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.61it/s] 7%|▋ | 2/28 [00:00<00:06, 4.08it/s] 11%|█ | 3/28 [00:00<00:06, 3.85it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.76it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.70it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.67it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.65it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.63it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.63it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.62it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.62it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.62it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.61it/s] 50%|█████ | 14/28 [00:03<00:03, 3.61it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.61it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.61it/s] 61%|██████ | 17/28 [00:04<00:03, 3.61it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.61it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.61it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.61it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.61it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.61it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.61it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.61it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.61it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.61it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.61it/s] 100%|██████████| 28/28 [00:07<00:00, 3.61it/s] 100%|██████████| 28/28 [00:07<00:00, 3.63it/s]Prediction
fofr/flux-90s-power-rangers:7088542bID2tgxv590sdrm60cj53nsnxwn70StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a low resolution vhs still from 90s POWER_RANGERS showing a green power ranger sitting in economy on a plane
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 3:2
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a low resolution vhs still from 90s POWER_RANGERS showing a green power ranger sitting in economy on a plane", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/flux-90s-power-rangers using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-90s-power-rangers:7088542b2b9917d09591dcc8062b60b42fd97f8e0d6cd2a53811bf911d7820fb", { input: { model: "dev", prompt: "a low resolution vhs still from 90s POWER_RANGERS showing a green power ranger sitting in economy on a plane", lora_scale: 1, num_outputs: 1, aspect_ratio: "3:2", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun fofr/flux-90s-power-rangers using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-90s-power-rangers:7088542b2b9917d09591dcc8062b60b42fd97f8e0d6cd2a53811bf911d7820fb", input={ "model": "dev", "prompt": "a low resolution vhs still from 90s POWER_RANGERS showing a green power ranger sitting in economy on a plane", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "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.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run fofr/flux-90s-power-rangers 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": "7088542b2b9917d09591dcc8062b60b42fd97f8e0d6cd2a53811bf911d7820fb", "input": { "model": "dev", "prompt": "a low resolution vhs still from 90s POWER_RANGERS showing a green power ranger sitting in economy on a plane", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "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": "2024-09-25T11:22:53.563278Z", "created_at": "2024-09-25T11:22:30.987000Z", "data_removed": false, "error": null, "id": "2tgxv590sdrm60cj53nsnxwn70", "input": { "model": "dev", "prompt": "a low resolution vhs still from 90s POWER_RANGERS showing a green power ranger sitting in economy on a plane", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 42882\nPrompt: a low resolution vhs still from 90s POWER_RANGERS showing a green power ranger sitting in economy on a plane\n[!] txt2img mode\nUsing dev model\nfree=7278203465728\nDownloading weights\n2024-09-25T11:22:36Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpel4bngh6/weights url=https://replicate.delivery/yhqm/EHj9imLybZ5JKBW3j89wd2Au641me8hYirfKAGnLNxYQZ4fmA/trained_model.tar\n2024-09-25T11:22:37Z | INFO | [ Complete ] dest=/tmp/tmpel4bngh6/weights size=\"172 MB\" total_elapsed=1.055s url=https://replicate.delivery/yhqm/EHj9imLybZ5JKBW3j89wd2Au641me8hYirfKAGnLNxYQZ4fmA/trained_model.tar\nDownloaded weights in 1.09s\nLoaded LoRAs in 8.51s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.62it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.09it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.86it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.76it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.71it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.68it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.66it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.65it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.64it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.63it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.63it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.62it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.62it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.62it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.62it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.62it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.62it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.62it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.62it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.62it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.62it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.62it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.62it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.62it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.62it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.62it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.62it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.62it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.64it/s]", "metrics": { "predict_time": 16.720428116, "total_time": 22.576278 }, "output": [ "https://replicate.delivery/yhqm/nhJEVqDT686xC5lLCdJSr5UnxZlujBz4q5eA3yfuAAlNSagTA/out-0.webp" ], "started_at": "2024-09-25T11:22:36.842850Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/2tgxv590sdrm60cj53nsnxwn70", "cancel": "https://api.replicate.com/v1/predictions/2tgxv590sdrm60cj53nsnxwn70/cancel" }, "version": "7088542b2b9917d09591dcc8062b60b42fd97f8e0d6cd2a53811bf911d7820fb" }Generated inUsing seed: 42882 Prompt: a low resolution vhs still from 90s POWER_RANGERS showing a green power ranger sitting in economy on a plane [!] txt2img mode Using dev model free=7278203465728 Downloading weights 2024-09-25T11:22:36Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpel4bngh6/weights url=https://replicate.delivery/yhqm/EHj9imLybZ5JKBW3j89wd2Au641me8hYirfKAGnLNxYQZ4fmA/trained_model.tar 2024-09-25T11:22:37Z | INFO | [ Complete ] dest=/tmp/tmpel4bngh6/weights size="172 MB" total_elapsed=1.055s url=https://replicate.delivery/yhqm/EHj9imLybZ5JKBW3j89wd2Au641me8hYirfKAGnLNxYQZ4fmA/trained_model.tar Downloaded weights in 1.09s Loaded LoRAs in 8.51s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.62it/s] 7%|▋ | 2/28 [00:00<00:06, 4.09it/s] 11%|█ | 3/28 [00:00<00:06, 3.86it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.76it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.71it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.68it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.66it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.65it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.64it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.63it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.63it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.62it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.62it/s] 50%|█████ | 14/28 [00:03<00:03, 3.62it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.62it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.62it/s] 61%|██████ | 17/28 [00:04<00:03, 3.62it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.62it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.62it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.62it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.62it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.62it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.62it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.62it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.62it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.62it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.62it/s] 100%|██████████| 28/28 [00:07<00:00, 3.62it/s] 100%|██████████| 28/28 [00:07<00:00, 3.64it/s]
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