justmalhar / flux-thumbnails
Generate 16:9 Thumbnails. Use prefix - `Thumbnail in the style of TOK`
- Public
- 3.4K runs
-
H100
Prediction
justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8IDzaaekqj1r5rm00chebpskaberrStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Thumbnail in the style of TOK, top angle shot of men standing in lines from age 1 to 100 years, squid games, coord set, standing on a football ground with bright lights
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 100
- num_inference_steps
- 50
{ "model": "dev", "prompt": "Thumbnail in the style of TOK, top angle shot of men standing in lines from age 1 to 100 years, squid games, coord set, standing on a football ground with bright lights ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 50 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run justmalhar/flux-thumbnails using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8", { input: { model: "dev", prompt: "Thumbnail in the style of TOK, top angle shot of men standing in lines from age 1 to 100 years, squid games, coord set, standing on a football ground with bright lights ", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "webp", guidance_scale: 3.5, output_quality: 100, num_inference_steps: 50 } } ); // 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 justmalhar/flux-thumbnails using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8", input={ "model": "dev", "prompt": "Thumbnail in the style of TOK, top angle shot of men standing in lines from age 1 to 100 years, squid games, coord set, standing on a football ground with bright lights ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run justmalhar/flux-thumbnails 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": "justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8", "input": { "model": "dev", "prompt": "Thumbnail in the style of TOK, top angle shot of men standing in lines from age 1 to 100 years, squid games, coord set, standing on a football ground with bright lights ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-21T03:14:23.471622Z", "created_at": "2024-08-21T03:13:57.185000Z", "data_removed": false, "error": null, "id": "zaaekqj1r5rm00chebpskaberr", "input": { "model": "dev", "prompt": "Thumbnail in the style of TOK, top angle shot of men standing in lines from age 1 to 100 years, squid games, coord set, standing on a football ground with bright lights ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 50 }, "logs": "Using seed: 65143\nPrompt: Thumbnail in the style of TOK, top angle shot of men standing in lines from age 1 to 100 years, squid games, coord set, standing on a football ground with bright lights\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nEnsuring enough disk space...\nFree disk space: 9413320531968\nDownloading weights\n2024-08-21T03:13:57Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/97c19f42324058f7 url=https://replicate.delivery/yhqm/vLH3ZJVEeJ3SBanDU1Gp7nR3JZrYaIrLNMsIY7oD29jinXqJA/trained_model.tar\n2024-08-21T03:14:00Z | INFO | [ Complete ] dest=/src/weights-cache/97c19f42324058f7 size=\"172 MB\" total_elapsed=2.824s url=https://replicate.delivery/yhqm/vLH3ZJVEeJ3SBanDU1Gp7nR3JZrYaIrLNMsIY7oD29jinXqJA/trained_model.tar\nb''\nDownloaded weights in 2.8547394275665283 seconds\nLoRA weights loaded successfully\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.68it/s]\n 4%|▍ | 2/50 [00:00<00:11, 4.24it/s]\n 6%|▌ | 3/50 [00:00<00:11, 3.98it/s]\n 8%|▊ | 4/50 [00:01<00:11, 3.86it/s]\n 10%|█ | 5/50 [00:01<00:11, 3.80it/s]\n 12%|█▏ | 6/50 [00:01<00:11, 3.76it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.74it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.73it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.71it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.70it/s]\n 22%|██▏ | 11/50 [00:02<00:10, 3.70it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.70it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.69it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.69it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.70it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.70it/s]\n 34%|███▍ | 17/50 [00:04<00:08, 3.69it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.69it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.69it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.70it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.69it/s]\n 44%|████▍ | 22/50 [00:05<00:07, 3.69it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.69it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.69it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.69it/s]\n 52%|█████▏ | 26/50 [00:06<00:06, 3.69it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.69it/s]\n 56%|█████▌ | 28/50 [00:07<00:05, 3.69it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.68it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.68it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.69it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.69it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.69it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.68it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.69it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.69it/s]\n 74%|███████▍ | 37/50 [00:09<00:03, 3.69it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.68it/s]\n 78%|███████▊ | 39/50 [00:10<00:02, 3.69it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.69it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.68it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.68it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.68it/s]\n 88%|████████▊ | 44/50 [00:11<00:01, 3.69it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.68it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.68it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.68it/s]\n 96%|█████████▌| 48/50 [00:12<00:00, 3.69it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.68it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.68it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.70it/s]", "metrics": { "predict_time": 26.262191769, "total_time": 26.286622 }, "output": [ "https://replicate.delivery/yhqm/OZhwRv2rkOIIM548i0MAgeCWf3u0t8XVRIaq5VyYjPAP2wUTA/out-0.webp" ], "started_at": "2024-08-21T03:13:57.209430Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/zaaekqj1r5rm00chebpskaberr", "cancel": "https://api.replicate.com/v1/predictions/zaaekqj1r5rm00chebpskaberr/cancel" }, "version": "42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8" }Generated inUsing seed: 65143 Prompt: Thumbnail in the style of TOK, top angle shot of men standing in lines from age 1 to 100 years, squid games, coord set, standing on a football ground with bright lights txt2img mode Using dev model Loading LoRA weights Ensuring enough disk space... Free disk space: 9413320531968 Downloading weights 2024-08-21T03:13:57Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/97c19f42324058f7 url=https://replicate.delivery/yhqm/vLH3ZJVEeJ3SBanDU1Gp7nR3JZrYaIrLNMsIY7oD29jinXqJA/trained_model.tar 2024-08-21T03:14:00Z | INFO | [ Complete ] dest=/src/weights-cache/97c19f42324058f7 size="172 MB" total_elapsed=2.824s url=https://replicate.delivery/yhqm/vLH3ZJVEeJ3SBanDU1Gp7nR3JZrYaIrLNMsIY7oD29jinXqJA/trained_model.tar b'' Downloaded weights in 2.8547394275665283 seconds LoRA weights loaded successfully 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:13, 3.68it/s] 4%|▍ | 2/50 [00:00<00:11, 4.24it/s] 6%|▌ | 3/50 [00:00<00:11, 3.98it/s] 8%|▊ | 4/50 [00:01<00:11, 3.86it/s] 10%|█ | 5/50 [00:01<00:11, 3.80it/s] 12%|█▏ | 6/50 [00:01<00:11, 3.76it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.74it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.73it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.71it/s] 20%|██ | 10/50 [00:02<00:10, 3.70it/s] 22%|██▏ | 11/50 [00:02<00:10, 3.70it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.70it/s] 26%|██▌ | 13/50 [00:03<00:10, 3.69it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.69it/s] 30%|███ | 15/50 [00:04<00:09, 3.70it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.70it/s] 34%|███▍ | 17/50 [00:04<00:08, 3.69it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.69it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.69it/s] 40%|████ | 20/50 [00:05<00:08, 3.70it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.69it/s] 44%|████▍ | 22/50 [00:05<00:07, 3.69it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.69it/s] 48%|████▊ | 24/50 [00:06<00:07, 3.69it/s] 50%|█████ | 25/50 [00:06<00:06, 3.69it/s] 52%|█████▏ | 26/50 [00:06<00:06, 3.69it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.69it/s] 56%|█████▌ | 28/50 [00:07<00:05, 3.69it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.68it/s] 60%|██████ | 30/50 [00:08<00:05, 3.68it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.69it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.69it/s] 66%|██████▌ | 33/50 [00:08<00:04, 3.69it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.68it/s] 70%|███████ | 35/50 [00:09<00:04, 3.69it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.69it/s] 74%|███████▍ | 37/50 [00:09<00:03, 3.69it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.68it/s] 78%|███████▊ | 39/50 [00:10<00:02, 3.69it/s] 80%|████████ | 40/50 [00:10<00:02, 3.69it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.68it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.68it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.68it/s] 88%|████████▊ | 44/50 [00:11<00:01, 3.69it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.68it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.68it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.68it/s] 96%|█████████▌| 48/50 [00:12<00:00, 3.69it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.68it/s] 100%|██████████| 50/50 [00:13<00:00, 3.68it/s] 100%|██████████| 50/50 [00:13<00:00, 3.70it/s]Prediction
justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8IDez9ehpxpehrm40chebr91wpcw4StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Thumbnail in the style of TOK, close up shot of man, in the background is a cruise ship in gold color in the sea, text “$1 Million”, realistic
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 100
- num_inference_steps
- 25
{ "model": "dev", "prompt": "Thumbnail in the style of TOK, close up shot of man, in the background is a cruise ship in gold color in the sea, text “$1 Million”, realistic ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 25 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run justmalhar/flux-thumbnails using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8", { input: { model: "dev", prompt: "Thumbnail in the style of TOK, close up shot of man, in the background is a cruise ship in gold color in the sea, text “$1 Million”, realistic ", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "webp", guidance_scale: 3.5, output_quality: 100, num_inference_steps: 25 } } ); // 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 justmalhar/flux-thumbnails using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8", input={ "model": "dev", "prompt": "Thumbnail in the style of TOK, close up shot of man, in the background is a cruise ship in gold color in the sea, text “$1 Million”, realistic ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 25 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run justmalhar/flux-thumbnails 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": "justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8", "input": { "model": "dev", "prompt": "Thumbnail in the style of TOK, close up shot of man, in the background is a cruise ship in gold color in the sea, text “$1 Million”, realistic ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 25 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-21T03:18:09.295092Z", "created_at": "2024-08-21T03:17:43.668000Z", "data_removed": false, "error": null, "id": "ez9ehpxpehrm40chebr91wpcw4", "input": { "model": "dev", "prompt": "Thumbnail in the style of TOK, close up shot of man, in the background is a cruise ship in gold color in the sea, text “$1 Million”, realistic ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 25 }, "logs": "Using seed: 24691\nPrompt: Thumbnail in the style of TOK, close up shot of man, in the background is a cruise ship in gold color in the sea, text “$1 Million”, realistic\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nEnsuring enough disk space...\nFree disk space: 9936800763904\nDownloading weights\n2024-08-21T03:17:43Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/97c19f42324058f7 url=https://replicate.delivery/yhqm/vLH3ZJVEeJ3SBanDU1Gp7nR3JZrYaIrLNMsIY7oD29jinXqJA/trained_model.tar\n2024-08-21T03:17:46Z | INFO | [ Complete ] dest=/src/weights-cache/97c19f42324058f7 size=\"172 MB\" total_elapsed=2.425s url=https://replicate.delivery/yhqm/vLH3ZJVEeJ3SBanDU1Gp7nR3JZrYaIrLNMsIY7oD29jinXqJA/trained_model.tar\nb''\nDownloaded weights in 2.4540672302246094 seconds\nLoRA weights loaded successfully\n 0%| | 0/25 [00:00<?, ?it/s]\n 4%|▍ | 1/25 [00:00<00:06, 3.69it/s]\n 8%|▊ | 2/25 [00:00<00:05, 4.26it/s]\n 12%|█▏ | 3/25 [00:00<00:05, 4.00it/s]\n 16%|█▌ | 4/25 [00:01<00:05, 3.87it/s]\n 20%|██ | 5/25 [00:01<00:05, 3.80it/s]\n 24%|██▍ | 6/25 [00:01<00:05, 3.77it/s]\n 28%|██▊ | 7/25 [00:01<00:04, 3.76it/s]\n 32%|███▏ | 8/25 [00:02<00:04, 3.74it/s]\n 36%|███▌ | 9/25 [00:02<00:04, 3.73it/s]\n 40%|████ | 10/25 [00:02<00:04, 3.72it/s]\n 44%|████▍ | 11/25 [00:02<00:03, 3.72it/s]\n 48%|████▊ | 12/25 [00:03<00:03, 3.72it/s]\n 52%|█████▏ | 13/25 [00:03<00:03, 3.71it/s]\n 56%|█████▌ | 14/25 [00:03<00:02, 3.72it/s]\n 60%|██████ | 15/25 [00:03<00:02, 3.72it/s]\n 64%|██████▍ | 16/25 [00:04<00:02, 3.71it/s]\n 68%|██████▊ | 17/25 [00:04<00:02, 3.71it/s]\n 72%|███████▏ | 18/25 [00:04<00:01, 3.71it/s]\n 76%|███████▌ | 19/25 [00:05<00:01, 3.71it/s]\n 80%|████████ | 20/25 [00:05<00:01, 3.71it/s]\n 84%|████████▍ | 21/25 [00:05<00:01, 3.71it/s]\n 88%|████████▊ | 22/25 [00:05<00:00, 3.71it/s]\n 92%|█████████▏| 23/25 [00:06<00:00, 3.72it/s]\n 96%|█████████▌| 24/25 [00:06<00:00, 3.71it/s]\n100%|██████████| 25/25 [00:06<00:00, 3.71it/s]\n100%|██████████| 25/25 [00:06<00:00, 3.74it/s]", "metrics": { "predict_time": 25.604790912, "total_time": 25.627092 }, "output": [ "https://replicate.delivery/yhqm/ChsiCX0Qu7JhBpu8sneq7sXfEMrMzSK4XiMz4jbBPLhx5wUTA/out-0.webp" ], "started_at": "2024-08-21T03:17:43.690302Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/ez9ehpxpehrm40chebr91wpcw4", "cancel": "https://api.replicate.com/v1/predictions/ez9ehpxpehrm40chebr91wpcw4/cancel" }, "version": "42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8" }Generated inUsing seed: 24691 Prompt: Thumbnail in the style of TOK, close up shot of man, in the background is a cruise ship in gold color in the sea, text “$1 Million”, realistic txt2img mode Using dev model Loading LoRA weights Ensuring enough disk space... Free disk space: 9936800763904 Downloading weights 2024-08-21T03:17:43Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/97c19f42324058f7 url=https://replicate.delivery/yhqm/vLH3ZJVEeJ3SBanDU1Gp7nR3JZrYaIrLNMsIY7oD29jinXqJA/trained_model.tar 2024-08-21T03:17:46Z | INFO | [ Complete ] dest=/src/weights-cache/97c19f42324058f7 size="172 MB" total_elapsed=2.425s url=https://replicate.delivery/yhqm/vLH3ZJVEeJ3SBanDU1Gp7nR3JZrYaIrLNMsIY7oD29jinXqJA/trained_model.tar b'' Downloaded weights in 2.4540672302246094 seconds LoRA weights loaded successfully 0%| | 0/25 [00:00<?, ?it/s] 4%|▍ | 1/25 [00:00<00:06, 3.69it/s] 8%|▊ | 2/25 [00:00<00:05, 4.26it/s] 12%|█▏ | 3/25 [00:00<00:05, 4.00it/s] 16%|█▌ | 4/25 [00:01<00:05, 3.87it/s] 20%|██ | 5/25 [00:01<00:05, 3.80it/s] 24%|██▍ | 6/25 [00:01<00:05, 3.77it/s] 28%|██▊ | 7/25 [00:01<00:04, 3.76it/s] 32%|███▏ | 8/25 [00:02<00:04, 3.74it/s] 36%|███▌ | 9/25 [00:02<00:04, 3.73it/s] 40%|████ | 10/25 [00:02<00:04, 3.72it/s] 44%|████▍ | 11/25 [00:02<00:03, 3.72it/s] 48%|████▊ | 12/25 [00:03<00:03, 3.72it/s] 52%|█████▏ | 13/25 [00:03<00:03, 3.71it/s] 56%|█████▌ | 14/25 [00:03<00:02, 3.72it/s] 60%|██████ | 15/25 [00:03<00:02, 3.72it/s] 64%|██████▍ | 16/25 [00:04<00:02, 3.71it/s] 68%|██████▊ | 17/25 [00:04<00:02, 3.71it/s] 72%|███████▏ | 18/25 [00:04<00:01, 3.71it/s] 76%|███████▌ | 19/25 [00:05<00:01, 3.71it/s] 80%|████████ | 20/25 [00:05<00:01, 3.71it/s] 84%|████████▍ | 21/25 [00:05<00:01, 3.71it/s] 88%|████████▊ | 22/25 [00:05<00:00, 3.71it/s] 92%|█████████▏| 23/25 [00:06<00:00, 3.72it/s] 96%|█████████▌| 24/25 [00:06<00:00, 3.71it/s] 100%|██████████| 25/25 [00:06<00:00, 3.71it/s] 100%|██████████| 25/25 [00:06<00:00, 3.74it/s]Prediction
justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8IDard3z5fw9srm00chhmwteptftwStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- schnell
- prompt
- Thumbnail in the style of TOK, a girl in red nike outfit standing in front of a 500 million dollar mansion, gold aesthetic, with text “$1 vs $500 Million Dollar Houses”
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 100
- num_inference_steps
- 4
{ "model": "schnell", "prompt": "Thumbnail in the style of TOK, a girl in red nike outfit standing in front of a 500 million dollar mansion, gold aesthetic, with text “$1 vs $500 Million Dollar Houses”", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 4 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run justmalhar/flux-thumbnails using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8", { input: { model: "schnell", prompt: "Thumbnail in the style of TOK, a girl in red nike outfit standing in front of a 500 million dollar mansion, gold aesthetic, with text “$1 vs $500 Million Dollar Houses”", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "webp", guidance_scale: 3.5, output_quality: 100, num_inference_steps: 4 } } ); // 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 justmalhar/flux-thumbnails using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8", input={ "model": "schnell", "prompt": "Thumbnail in the style of TOK, a girl in red nike outfit standing in front of a 500 million dollar mansion, gold aesthetic, with text “$1 vs $500 Million Dollar Houses”", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 4 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run justmalhar/flux-thumbnails 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": "justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8", "input": { "model": "schnell", "prompt": "Thumbnail in the style of TOK, a girl in red nike outfit standing in front of a 500 million dollar mansion, gold aesthetic, with text “$1 vs $500 Million Dollar Houses”", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 4 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T05:48:06.000097Z", "created_at": "2024-08-26T05:47:53.294000Z", "data_removed": false, "error": null, "id": "ard3z5fw9srm00chhmwteptftw", "input": { "model": "schnell", "prompt": "Thumbnail in the style of TOK, a girl in red nike outfit standing in front of a 500 million dollar mansion, gold aesthetic, with text “$1 vs $500 Million Dollar Houses”", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 4 }, "logs": "Using seed: 53408\nPrompt: Thumbnail in the style of TOK, a girl in red nike outfit standing in front of a 500 million dollar mansion, gold aesthetic, with text “$1 vs $500 Million Dollar Houses”\ntxt2img mode\nUsing schnell model\nfree=9892826619904\nDownloading weights\n2024-08-26T05:47:53Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpc5heiv_9/weights url=https://replicate.delivery/yhqm/vLH3ZJVEeJ3SBanDU1Gp7nR3JZrYaIrLNMsIY7oD29jinXqJA/trained_model.tar\n2024-08-26T05:47:55Z | INFO | [ Complete ] dest=/tmp/tmpc5heiv_9/weights size=\"172 MB\" total_elapsed=1.617s url=https://replicate.delivery/yhqm/vLH3ZJVEeJ3SBanDU1Gp7nR3JZrYaIrLNMsIY7oD29jinXqJA/trained_model.tar\nDownloaded weights in 1.65s\nLoaded LoRAs in 10.95s\n 0%| | 0/4 [00:00<?, ?it/s]\n 25%|██▌ | 1/4 [00:00<00:00, 3.86it/s]\n 50%|█████ | 2/4 [00:00<00:00, 4.44it/s]\n 75%|███████▌ | 3/4 [00:00<00:00, 4.17it/s]\n100%|██████████| 4/4 [00:00<00:00, 4.06it/s]\n100%|██████████| 4/4 [00:00<00:00, 4.10it/s]", "metrics": { "predict_time": 12.492995191, "total_time": 12.706097 }, "output": [ "https://replicate.delivery/yhqm/WJSWUDmxNSphNZyuUwHizmkxeCjqpPjRmzN13OMYv94KSOrJA/out-0.webp" ], "started_at": "2024-08-26T05:47:53.507102Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/ard3z5fw9srm00chhmwteptftw", "cancel": "https://api.replicate.com/v1/predictions/ard3z5fw9srm00chhmwteptftw/cancel" }, "version": "42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8" }Generated inUsing seed: 53408 Prompt: Thumbnail in the style of TOK, a girl in red nike outfit standing in front of a 500 million dollar mansion, gold aesthetic, with text “$1 vs $500 Million Dollar Houses” txt2img mode Using schnell model free=9892826619904 Downloading weights 2024-08-26T05:47:53Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpc5heiv_9/weights url=https://replicate.delivery/yhqm/vLH3ZJVEeJ3SBanDU1Gp7nR3JZrYaIrLNMsIY7oD29jinXqJA/trained_model.tar 2024-08-26T05:47:55Z | INFO | [ Complete ] dest=/tmp/tmpc5heiv_9/weights size="172 MB" total_elapsed=1.617s url=https://replicate.delivery/yhqm/vLH3ZJVEeJ3SBanDU1Gp7nR3JZrYaIrLNMsIY7oD29jinXqJA/trained_model.tar Downloaded weights in 1.65s Loaded LoRAs in 10.95s 0%| | 0/4 [00:00<?, ?it/s] 25%|██▌ | 1/4 [00:00<00:00, 3.86it/s] 50%|█████ | 2/4 [00:00<00:00, 4.44it/s] 75%|███████▌ | 3/4 [00:00<00:00, 4.17it/s] 100%|██████████| 4/4 [00:00<00:00, 4.06it/s] 100%|██████████| 4/4 [00:00<00:00, 4.10it/s]Prediction
justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8IDe40sc4y81hrm40chhmxs1scvkrStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- schnell
- prompt
- Thumbnail in the style of TOK, man in. Reality show set with 100 prisoners standing in front with scared face, orange clothes for prisoners, jail aesthetic, challenge video; with text “ Who makes out alive?”
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 100
- num_inference_steps
- 4
{ "model": "schnell", "prompt": "Thumbnail in the style of TOK, man in. Reality show set with 100 prisoners standing in front with scared face, orange clothes for prisoners, jail aesthetic, challenge video; with text “ Who makes out alive?”", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 4 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run justmalhar/flux-thumbnails using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8", { input: { model: "schnell", prompt: "Thumbnail in the style of TOK, man in. Reality show set with 100 prisoners standing in front with scared face, orange clothes for prisoners, jail aesthetic, challenge video; with text “ Who makes out alive?”", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "webp", guidance_scale: 3.5, output_quality: 100, num_inference_steps: 4 } } ); // 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 justmalhar/flux-thumbnails using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8", input={ "model": "schnell", "prompt": "Thumbnail in the style of TOK, man in. Reality show set with 100 prisoners standing in front with scared face, orange clothes for prisoners, jail aesthetic, challenge video; with text “ Who makes out alive?”", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 4 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run justmalhar/flux-thumbnails 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": "justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8", "input": { "model": "schnell", "prompt": "Thumbnail in the style of TOK, man in. Reality show set with 100 prisoners standing in front with scared face, orange clothes for prisoners, jail aesthetic, challenge video; with text “ Who makes out alive?”", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 4 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T05:50:01.424928Z", "created_at": "2024-08-26T05:49:50.988000Z", "data_removed": false, "error": null, "id": "e40sc4y81hrm40chhmxs1scvkr", "input": { "model": "schnell", "prompt": "Thumbnail in the style of TOK, man in. Reality show set with 100 prisoners standing in front with scared face, orange clothes for prisoners, jail aesthetic, challenge video; with text “ Who makes out alive?”", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 4 }, "logs": "Using seed: 53493\nPrompt: Thumbnail in the style of TOK, man in. Reality show set with 100 prisoners standing in front with scared face, orange clothes for prisoners, jail aesthetic, challenge video; with text “ Who makes out alive?”\ntxt2img mode\nUsing schnell model\nLoaded LoRAs in 8.88s\n 0%| | 0/4 [00:00<?, ?it/s]\n 25%|██▌ | 1/4 [00:00<00:00, 3.91it/s]\n 50%|█████ | 2/4 [00:00<00:00, 4.50it/s]\n 75%|███████▌ | 3/4 [00:00<00:00, 4.21it/s]\n100%|██████████| 4/4 [00:00<00:00, 4.10it/s]\n100%|██████████| 4/4 [00:00<00:00, 4.15it/s]", "metrics": { "predict_time": 10.427106287, "total_time": 10.436928 }, "output": [ "https://replicate.delivery/yhqm/88JXfey52jncgErc5gzMgWnokgrs6DXUYfbst4zML3zSM5smA/out-0.webp" ], "started_at": "2024-08-26T05:49:50.997822Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/e40sc4y81hrm40chhmxs1scvkr", "cancel": "https://api.replicate.com/v1/predictions/e40sc4y81hrm40chhmxs1scvkr/cancel" }, "version": "42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8" }Generated inUsing seed: 53493 Prompt: Thumbnail in the style of TOK, man in. Reality show set with 100 prisoners standing in front with scared face, orange clothes for prisoners, jail aesthetic, challenge video; with text “ Who makes out alive?” txt2img mode Using schnell model Loaded LoRAs in 8.88s 0%| | 0/4 [00:00<?, ?it/s] 25%|██▌ | 1/4 [00:00<00:00, 3.91it/s] 50%|█████ | 2/4 [00:00<00:00, 4.50it/s] 75%|███████▌ | 3/4 [00:00<00:00, 4.21it/s] 100%|██████████| 4/4 [00:00<00:00, 4.10it/s] 100%|██████████| 4/4 [00:00<00:00, 4.15it/s]Prediction
justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8IDzbpzkgdya5rm60chf5xawh0bq4StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Thumbnail in the style of TOK, A map of the Korean Sophie with yellow barbed wire around it, text "security" in black on top and red for North Korea border saying that escape is no longer possible. Text below says " replicate north korea . The word ' No Way' written at bottom right corner, text under small sign reading "may be". In white color font underneath showing South Sea to the south and Japan to west side of archipelago , aerial view of sea level to show water between two countries. colorful. Realistic. High resolution. --ar 128:61 —ar 16:9
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 16:9
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 100
- num_inference_steps
- 50
{ "model": "dev", "prompt": "Thumbnail in the style of TOK, A map of the Korean Sophie with yellow barbed wire around it, text \"security\" in black on top and red for North Korea border saying that escape is no longer possible. Text below says \" replicate north korea . The word ' No Way' written at bottom right corner, text under small sign reading \"may be\". In white color font underneath showing South Sea to the south and Japan to west side of archipelago , aerial view of sea level to show water between two countries. colorful. Realistic. High resolution. --ar 128:61 —ar 16:9", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 50 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run justmalhar/flux-thumbnails using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8", { input: { model: "dev", prompt: "Thumbnail in the style of TOK, A map of the Korean Sophie with yellow barbed wire around it, text \"security\" in black on top and red for North Korea border saying that escape is no longer possible. Text below says \" replicate north korea . The word ' No Way' written at bottom right corner, text under small sign reading \"may be\". In white color font underneath showing South Sea to the south and Japan to west side of archipelago , aerial view of sea level to show water between two countries. colorful. Realistic. High resolution. --ar 128:61 —ar 16:9", lora_scale: 1, num_outputs: 4, aspect_ratio: "16:9", output_format: "webp", guidance_scale: 3.5, output_quality: 100, num_inference_steps: 50 } } ); // 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 justmalhar/flux-thumbnails using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8", input={ "model": "dev", "prompt": "Thumbnail in the style of TOK, A map of the Korean Sophie with yellow barbed wire around it, text \"security\" in black on top and red for North Korea border saying that escape is no longer possible. Text below says \" replicate north korea . The word ' No Way' written at bottom right corner, text under small sign reading \"may be\". In white color font underneath showing South Sea to the south and Japan to west side of archipelago , aerial view of sea level to show water between two countries. colorful. Realistic. High resolution. --ar 128:61 —ar 16:9", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run justmalhar/flux-thumbnails 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": "justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8", "input": { "model": "dev", "prompt": "Thumbnail in the style of TOK, A map of the Korean Sophie with yellow barbed wire around it, text \\"security\\" in black on top and red for North Korea border saying that escape is no longer possible. Text below says \\" replicate north korea . The word \' No Way\' written at bottom right corner, text under small sign reading \\"may be\\". In white color font underneath showing South Sea to the south and Japan to west side of archipelago , aerial view of sea level to show water between two countries. colorful. Realistic. High resolution. --ar 128:61 —ar 16:9", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-22T09:47:19.155955Z", "created_at": "2024-08-22T09:46:12.945000Z", "data_removed": false, "error": null, "id": "zbpzkgdya5rm60chf5xawh0bq4", "input": { "model": "dev", "prompt": "Thumbnail in the style of TOK, A map of the Korean Sophie with yellow barbed wire around it, text \"security\" in black on top and red for North Korea border saying that escape is no longer possible. Text below says \" replicate north korea . The word ' No Way' written at bottom right corner, text under small sign reading \"may be\". In white color font underneath showing South Sea to the south and Japan to west side of archipelago , aerial view of sea level to show water between two countries. colorful. Realistic. High resolution. --ar 128:61 —ar 16:9", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 50 }, "logs": "Using seed: 12479\nPrompt: Thumbnail in the style of TOK, A map of the Korean Sophie with yellow barbed wire around it, text \"security\" in black on top and red for North Korea border saying that escape is no longer possible. Text below says \" replicate north korea . The word ' No Way' written at bottom right corner, text under small sign reading \"may be\". In white color font underneath showing South Sea to the south and Japan to west side of archipelago , aerial view of sea level to show water between two countries. colorful. Realistic. High resolution. --ar 128:61 —ar 16:9\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nEnsuring enough disk space...\nFree disk space: 9649564880896\nDownloading weights\n2024-08-22T09:46:17Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/97c19f42324058f7 url=https://replicate.delivery/yhqm/vLH3ZJVEeJ3SBanDU1Gp7nR3JZrYaIrLNMsIY7oD29jinXqJA/trained_model.tar\n2024-08-22T09:46:18Z | INFO | [ Complete ] dest=/src/weights-cache/97c19f42324058f7 size=\"172 MB\" total_elapsed=1.452s url=https://replicate.delivery/yhqm/vLH3ZJVEeJ3SBanDU1Gp7nR3JZrYaIrLNMsIY7oD29jinXqJA/trained_model.tar\nb''\nDownloaded weights in 1.487677812576294 seconds\nLoRA weights loaded successfully\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['color font underneath showing south sea to the south and japan to west side of archipelago, aerial view of sea level to show water between two countries. colorful. realistic. high resolution. -- ar 1 2 8 : 6 1 — ar 1 6 : 9', 'color font underneath showing south sea to the south and japan to west side of archipelago, aerial view of sea level to show water between two countries. colorful. realistic. high resolution. -- ar 1 2 8 : 6 1 — ar 1 6 : 9', 'color font underneath showing south sea to the south and japan to west side of archipelago, aerial view of sea level to show water between two countries. colorful. realistic. high resolution. -- ar 1 2 8 : 6 1 — ar 1 6 : 9', 'color font underneath showing south sea to the south and japan to west side of archipelago, aerial view of sea level to show water between two countries. colorful. realistic. high resolution. -- ar 1 2 8 : 6 1 — ar 1 6 : 9']\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:48, 1.00it/s]\n 4%|▍ | 2/50 [00:01<00:41, 1.15it/s]\n 6%|▌ | 3/50 [00:02<00:43, 1.08it/s]\n 8%|▊ | 4/50 [00:03<00:43, 1.05it/s]\n 10%|█ | 5/50 [00:04<00:43, 1.03it/s]\n 12%|█▏ | 6/50 [00:05<00:43, 1.02it/s]\n 14%|█▍ | 7/50 [00:06<00:42, 1.01it/s]\n 16%|█▌ | 8/50 [00:07<00:41, 1.01it/s]\n 18%|█▊ | 9/50 [00:08<00:40, 1.01it/s]\n 20%|██ | 10/50 [00:09<00:39, 1.01it/s]\n 22%|██▏ | 11/50 [00:10<00:38, 1.00it/s]\n 24%|██▍ | 12/50 [00:11<00:37, 1.00it/s]\n 26%|██▌ | 13/50 [00:12<00:36, 1.00it/s]\n 28%|██▊ | 14/50 [00:13<00:35, 1.00it/s]\n 30%|███ | 15/50 [00:14<00:34, 1.00it/s]\n 32%|███▏ | 16/50 [00:15<00:33, 1.00it/s]\n 34%|███▍ | 17/50 [00:16<00:32, 1.00it/s]\n 36%|███▌ | 18/50 [00:17<00:31, 1.00it/s]\n 38%|███▊ | 19/50 [00:18<00:30, 1.00it/s]\n 40%|████ | 20/50 [00:19<00:30, 1.00s/it]\n 42%|████▏ | 21/50 [00:20<00:29, 1.00s/it]\n 44%|████▍ | 22/50 [00:21<00:28, 1.00s/it]\n 46%|████▌ | 23/50 [00:22<00:27, 1.00s/it]\n 48%|████▊ | 24/50 [00:23<00:26, 1.00s/it]\n 50%|█████ | 25/50 [00:24<00:25, 1.00s/it]\n 52%|█████▏ | 26/50 [00:25<00:24, 1.01s/it]\n 54%|█████▍ | 27/50 [00:26<00:23, 1.00s/it]\n 56%|█████▌ | 28/50 [00:27<00:22, 1.01s/it]\n 58%|█████▊ | 29/50 [00:28<00:21, 1.00s/it]\n 60%|██████ | 30/50 [00:29<00:20, 1.01s/it]\n 62%|██████▏ | 31/50 [00:30<00:19, 1.00s/it]\n 64%|██████▍ | 32/50 [00:31<00:18, 1.00s/it]\n 66%|██████▌ | 33/50 [00:32<00:17, 1.00s/it]\n 68%|██████▊ | 34/50 [00:33<00:16, 1.00s/it]\n 70%|███████ | 35/50 [00:34<00:15, 1.00s/it]\n 72%|███████▏ | 36/50 [00:35<00:14, 1.00s/it]\n 74%|███████▍ | 37/50 [00:36<00:13, 1.00s/it]\n 76%|███████▌ | 38/50 [00:37<00:12, 1.00s/it]\n 78%|███████▊ | 39/50 [00:38<00:11, 1.01s/it]\n 80%|████████ | 40/50 [00:39<00:10, 1.00s/it]\n 82%|████████▏ | 41/50 [00:40<00:09, 1.01s/it]\n 84%|████████▍ | 42/50 [00:41<00:08, 1.01s/it]\n 86%|████████▌ | 43/50 [00:42<00:07, 1.01s/it]\n 88%|████████▊ | 44/50 [00:43<00:06, 1.01s/it]\n 90%|█████████ | 45/50 [00:44<00:05, 1.01s/it]\n 92%|█████████▏| 46/50 [00:45<00:04, 1.01s/it]\n 94%|█████████▍| 47/50 [00:46<00:03, 1.01s/it]\n 96%|█████████▌| 48/50 [00:47<00:02, 1.01s/it]\n 98%|█████████▊| 49/50 [00:48<00:01, 1.01s/it]\n100%|██████████| 50/50 [00:49<00:00, 1.01s/it]\n100%|██████████| 50/50 [00:49<00:00, 1.00it/s]", "metrics": { "predict_time": 61.697797044, "total_time": 66.210955 }, "output": [ "https://replicate.delivery/yhqm/JK4W5oHrHxauNJyVpgfiAcAYYyA3qhZX7Wv1ne5CeTZNZXqmA/out-0.webp", "https://replicate.delivery/yhqm/4KCUgLRulKKeBCd4ex6LAT7hPlxFXgIOUrfykzKsEIaMZXqmA/out-1.webp", "https://replicate.delivery/yhqm/qBMR1fxGVh3eepidqPlgBp19jjNvs9cU6Fiz93aoSbqMZXqmA/out-2.webp", "https://replicate.delivery/yhqm/mUoRTr4XT86dPNezdhgfE0Enf1s7RN95kAHPkAXezt4cyuUNB/out-3.webp" ], "started_at": "2024-08-22T09:46:17.458158Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/zbpzkgdya5rm60chf5xawh0bq4", "cancel": "https://api.replicate.com/v1/predictions/zbpzkgdya5rm60chf5xawh0bq4/cancel" }, "version": "42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8" }Generated inUsing seed: 12479 Prompt: Thumbnail in the style of TOK, A map of the Korean Sophie with yellow barbed wire around it, text "security" in black on top and red for North Korea border saying that escape is no longer possible. Text below says " replicate north korea . The word ' No Way' written at bottom right corner, text under small sign reading "may be". In white color font underneath showing South Sea to the south and Japan to west side of archipelago , aerial view of sea level to show water between two countries. colorful. Realistic. High resolution. --ar 128:61 —ar 16:9 txt2img mode Using dev model Loading LoRA weights Ensuring enough disk space... Free disk space: 9649564880896 Downloading weights 2024-08-22T09:46:17Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/97c19f42324058f7 url=https://replicate.delivery/yhqm/vLH3ZJVEeJ3SBanDU1Gp7nR3JZrYaIrLNMsIY7oD29jinXqJA/trained_model.tar 2024-08-22T09:46:18Z | INFO | [ Complete ] dest=/src/weights-cache/97c19f42324058f7 size="172 MB" total_elapsed=1.452s url=https://replicate.delivery/yhqm/vLH3ZJVEeJ3SBanDU1Gp7nR3JZrYaIrLNMsIY7oD29jinXqJA/trained_model.tar b'' Downloaded weights in 1.487677812576294 seconds LoRA weights loaded successfully The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['color font underneath showing south sea to the south and japan to west side of archipelago, aerial view of sea level to show water between two countries. colorful. realistic. high resolution. -- ar 1 2 8 : 6 1 — ar 1 6 : 9', 'color font underneath showing south sea to the south and japan to west side of archipelago, aerial view of sea level to show water between two countries. colorful. realistic. high resolution. -- ar 1 2 8 : 6 1 — ar 1 6 : 9', 'color font underneath showing south sea to the south and japan to west side of archipelago, aerial view of sea level to show water between two countries. colorful. realistic. high resolution. -- ar 1 2 8 : 6 1 — ar 1 6 : 9', 'color font underneath showing south sea to the south and japan to west side of archipelago, aerial view of sea level to show water between two countries. colorful. realistic. high resolution. -- ar 1 2 8 : 6 1 — ar 1 6 : 9'] 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:48, 1.00it/s] 4%|▍ | 2/50 [00:01<00:41, 1.15it/s] 6%|▌ | 3/50 [00:02<00:43, 1.08it/s] 8%|▊ | 4/50 [00:03<00:43, 1.05it/s] 10%|█ | 5/50 [00:04<00:43, 1.03it/s] 12%|█▏ | 6/50 [00:05<00:43, 1.02it/s] 14%|█▍ | 7/50 [00:06<00:42, 1.01it/s] 16%|█▌ | 8/50 [00:07<00:41, 1.01it/s] 18%|█▊ | 9/50 [00:08<00:40, 1.01it/s] 20%|██ | 10/50 [00:09<00:39, 1.01it/s] 22%|██▏ | 11/50 [00:10<00:38, 1.00it/s] 24%|██▍ | 12/50 [00:11<00:37, 1.00it/s] 26%|██▌ | 13/50 [00:12<00:36, 1.00it/s] 28%|██▊ | 14/50 [00:13<00:35, 1.00it/s] 30%|███ | 15/50 [00:14<00:34, 1.00it/s] 32%|███▏ | 16/50 [00:15<00:33, 1.00it/s] 34%|███▍ | 17/50 [00:16<00:32, 1.00it/s] 36%|███▌ | 18/50 [00:17<00:31, 1.00it/s] 38%|███▊ | 19/50 [00:18<00:30, 1.00it/s] 40%|████ | 20/50 [00:19<00:30, 1.00s/it] 42%|████▏ | 21/50 [00:20<00:29, 1.00s/it] 44%|████▍ | 22/50 [00:21<00:28, 1.00s/it] 46%|████▌ | 23/50 [00:22<00:27, 1.00s/it] 48%|████▊ | 24/50 [00:23<00:26, 1.00s/it] 50%|█████ | 25/50 [00:24<00:25, 1.00s/it] 52%|█████▏ | 26/50 [00:25<00:24, 1.01s/it] 54%|█████▍ | 27/50 [00:26<00:23, 1.00s/it] 56%|█████▌ | 28/50 [00:27<00:22, 1.01s/it] 58%|█████▊ | 29/50 [00:28<00:21, 1.00s/it] 60%|██████ | 30/50 [00:29<00:20, 1.01s/it] 62%|██████▏ | 31/50 [00:30<00:19, 1.00s/it] 64%|██████▍ | 32/50 [00:31<00:18, 1.00s/it] 66%|██████▌ | 33/50 [00:32<00:17, 1.00s/it] 68%|██████▊ | 34/50 [00:33<00:16, 1.00s/it] 70%|███████ | 35/50 [00:34<00:15, 1.00s/it] 72%|███████▏ | 36/50 [00:35<00:14, 1.00s/it] 74%|███████▍ | 37/50 [00:36<00:13, 1.00s/it] 76%|███████▌ | 38/50 [00:37<00:12, 1.00s/it] 78%|███████▊ | 39/50 [00:38<00:11, 1.01s/it] 80%|████████ | 40/50 [00:39<00:10, 1.00s/it] 82%|████████▏ | 41/50 [00:40<00:09, 1.01s/it] 84%|████████▍ | 42/50 [00:41<00:08, 1.01s/it] 86%|████████▌ | 43/50 [00:42<00:07, 1.01s/it] 88%|████████▊ | 44/50 [00:43<00:06, 1.01s/it] 90%|█████████ | 45/50 [00:44<00:05, 1.01s/it] 92%|█████████▏| 46/50 [00:45<00:04, 1.01s/it] 94%|█████████▍| 47/50 [00:46<00:03, 1.01s/it] 96%|█████████▌| 48/50 [00:47<00:02, 1.01s/it] 98%|█████████▊| 49/50 [00:48<00:01, 1.01s/it] 100%|██████████| 50/50 [00:49<00:00, 1.01s/it] 100%|██████████| 50/50 [00:49<00:00, 1.00it/s]Prediction
justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8ID29vm0jy8wdrm40cheb4sfp7z6rStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Thumbnail in the style of TOK, A young woman with long black hair is posing in front of a green football field with glowing lights, displaying text "You won’t believe this…”, She smiles at camera. The background features one to two thousand fans. In detail style. Realistic photography
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 100
- num_inference_steps
- 50
{ "model": "dev", "prompt": "Thumbnail in the style of TOK, A young woman with long black hair is posing in front of a green football field with glowing lights, displaying text \"You won’t believe this…”, She smiles at camera. The background features one to two thousand fans. In detail style. Realistic photography", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 50 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run justmalhar/flux-thumbnails using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8", { input: { model: "dev", prompt: "Thumbnail in the style of TOK, A young woman with long black hair is posing in front of a green football field with glowing lights, displaying text \"You won’t believe this…”, She smiles at camera. The background features one to two thousand fans. In detail style. Realistic photography", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "webp", guidance_scale: 3.5, output_quality: 100, num_inference_steps: 50 } } ); // 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 justmalhar/flux-thumbnails using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8", input={ "model": "dev", "prompt": "Thumbnail in the style of TOK, A young woman with long black hair is posing in front of a green football field with glowing lights, displaying text \"You won’t believe this…”, She smiles at camera. The background features one to two thousand fans. In detail style. Realistic photography", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run justmalhar/flux-thumbnails 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": "justmalhar/flux-thumbnails:42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8", "input": { "model": "dev", "prompt": "Thumbnail in the style of TOK, A young woman with long black hair is posing in front of a green football field with glowing lights, displaying text \\"You won’t believe this…”, She smiles at camera. The background features one to two thousand fans. In detail style. Realistic photography", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-21T02:35:37.573934Z", "created_at": "2024-08-21T02:35:12.483000Z", "data_removed": false, "error": null, "id": "29vm0jy8wdrm40cheb4sfp7z6r", "input": { "model": "dev", "prompt": "Thumbnail in the style of TOK, A young woman with long black hair is posing in front of a green football field with glowing lights, displaying text \"You won’t believe this…”, She smiles at camera. The background features one to two thousand fans. In detail style. Realistic photography", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 50 }, "logs": "Using seed: 20163\nPrompt: Thumbnail in the style of TOK, A young woman with long black hair is posing in front of a green football field with glowing lights, displaying text \"You won’t believe this…”, She smiles at camera. The background features one to two thousand fans. In detail style. Realistic photography\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nEnsuring enough disk space...\nFree disk space: 9629617389568\nDownloading weights\n2024-08-21T02:35:12Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/97c19f42324058f7 url=https://replicate.delivery/yhqm/vLH3ZJVEeJ3SBanDU1Gp7nR3JZrYaIrLNMsIY7oD29jinXqJA/trained_model.tar\n2024-08-21T02:35:15Z | INFO | [ Complete ] dest=/src/weights-cache/97c19f42324058f7 size=\"172 MB\" total_elapsed=2.467s url=https://replicate.delivery/yhqm/vLH3ZJVEeJ3SBanDU1Gp7nR3JZrYaIrLNMsIY7oD29jinXqJA/trained_model.tar\nb''\nDownloaded weights in 2.495424509048462 seconds\nLoRA weights loaded successfully\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.67it/s]\n 4%|▍ | 2/50 [00:00<00:11, 4.24it/s]\n 6%|▌ | 3/50 [00:00<00:11, 3.97it/s]\n 8%|▊ | 4/50 [00:01<00:11, 3.85it/s]\n 10%|█ | 5/50 [00:01<00:11, 3.78it/s]\n 12%|█▏ | 6/50 [00:01<00:11, 3.75it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.73it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.71it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.70it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.70it/s]\n 22%|██▏ | 11/50 [00:02<00:10, 3.70it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.68it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.68it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.69it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.69it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.69it/s]\n 34%|███▍ | 17/50 [00:04<00:08, 3.68it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.69it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.69it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.69it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.68it/s]\n 44%|████▍ | 22/50 [00:05<00:07, 3.69it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.69it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.69it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.68it/s]\n 52%|█████▏ | 26/50 [00:06<00:06, 3.69it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.69it/s]\n 56%|█████▌ | 28/50 [00:07<00:05, 3.68it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.68it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.69it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.69it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.68it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.68it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.69it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.69it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.68it/s]\n 74%|███████▍ | 37/50 [00:09<00:03, 3.68it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.68it/s]\n 78%|███████▊ | 39/50 [00:10<00:02, 3.69it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.68it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.68it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.68it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.69it/s]\n 88%|████████▊ | 44/50 [00:11<00:01, 3.68it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.68it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.68it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.69it/s]\n 96%|█████████▌| 48/50 [00:12<00:00, 3.68it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.68it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.69it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.70it/s]", "metrics": { "predict_time": 25.05901742, "total_time": 25.090934 }, "output": [ "https://replicate.delivery/yhqm/JH5ny73FTiKeEStmQlwM7y1v8t0ZbksMhI05EpBfTML5RwUTA/out-0.webp" ], "started_at": "2024-08-21T02:35:12.514916Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/29vm0jy8wdrm40cheb4sfp7z6r", "cancel": "https://api.replicate.com/v1/predictions/29vm0jy8wdrm40cheb4sfp7z6r/cancel" }, "version": "42799c2b58e0a6ca82d3a1d90f655f6386542e325d2017e3256b092189f567b8" }Generated inUsing seed: 20163 Prompt: Thumbnail in the style of TOK, A young woman with long black hair is posing in front of a green football field with glowing lights, displaying text "You won’t believe this…”, She smiles at camera. The background features one to two thousand fans. In detail style. Realistic photography txt2img mode Using dev model Loading LoRA weights Ensuring enough disk space... Free disk space: 9629617389568 Downloading weights 2024-08-21T02:35:12Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/97c19f42324058f7 url=https://replicate.delivery/yhqm/vLH3ZJVEeJ3SBanDU1Gp7nR3JZrYaIrLNMsIY7oD29jinXqJA/trained_model.tar 2024-08-21T02:35:15Z | INFO | [ Complete ] dest=/src/weights-cache/97c19f42324058f7 size="172 MB" total_elapsed=2.467s url=https://replicate.delivery/yhqm/vLH3ZJVEeJ3SBanDU1Gp7nR3JZrYaIrLNMsIY7oD29jinXqJA/trained_model.tar b'' Downloaded weights in 2.495424509048462 seconds LoRA weights loaded successfully 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:13, 3.67it/s] 4%|▍ | 2/50 [00:00<00:11, 4.24it/s] 6%|▌ | 3/50 [00:00<00:11, 3.97it/s] 8%|▊ | 4/50 [00:01<00:11, 3.85it/s] 10%|█ | 5/50 [00:01<00:11, 3.78it/s] 12%|█▏ | 6/50 [00:01<00:11, 3.75it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.73it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.71it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.70it/s] 20%|██ | 10/50 [00:02<00:10, 3.70it/s] 22%|██▏ | 11/50 [00:02<00:10, 3.70it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.68it/s] 26%|██▌ | 13/50 [00:03<00:10, 3.68it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.69it/s] 30%|███ | 15/50 [00:04<00:09, 3.69it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.69it/s] 34%|███▍ | 17/50 [00:04<00:08, 3.68it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.69it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.69it/s] 40%|████ | 20/50 [00:05<00:08, 3.69it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.68it/s] 44%|████▍ | 22/50 [00:05<00:07, 3.69it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.69it/s] 48%|████▊ | 24/50 [00:06<00:07, 3.69it/s] 50%|█████ | 25/50 [00:06<00:06, 3.68it/s] 52%|█████▏ | 26/50 [00:06<00:06, 3.69it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.69it/s] 56%|█████▌ | 28/50 [00:07<00:05, 3.68it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.68it/s] 60%|██████ | 30/50 [00:08<00:05, 3.69it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.69it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.68it/s] 66%|██████▌ | 33/50 [00:08<00:04, 3.68it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.69it/s] 70%|███████ | 35/50 [00:09<00:04, 3.69it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.68it/s] 74%|███████▍ | 37/50 [00:09<00:03, 3.68it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.68it/s] 78%|███████▊ | 39/50 [00:10<00:02, 3.69it/s] 80%|████████ | 40/50 [00:10<00:02, 3.68it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.68it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.68it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.69it/s] 88%|████████▊ | 44/50 [00:11<00:01, 3.68it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.68it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.68it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.69it/s] 96%|█████████▌| 48/50 [00:12<00:00, 3.68it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.68it/s] 100%|██████████| 50/50 [00:13<00:00, 3.69it/s] 100%|██████████| 50/50 [00:13<00:00, 3.70it/s]
Want to make some of these yourself?
Run this model
