kondagen
/
flux-char-sud
- Public
- 8 runs
-
H100
Prediction
kondagen/flux-char-sud:5600053dIDfmn0p9mnw1rma0cmrwxtnt9b9wStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Medium close-up shot of SUD junior police officer in a brown Delhi Police uniform adorned with badges, insignia, and a police cap, speaking with focus and determination to the senior officer. Behind him, the white Delhi Police patrol vehicle with red and blue flashing lights is visible, creating a striking backdrop. The posh bar hotel with vibrant lights and luxury cars adds depth in the softly blurred midnight background, enhancing the cinematic tone with HDR quality
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- jpg
- guidance_scale
- 2.11
- output_quality
- 80
- prompt_strength
- 0.83
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": " Medium close-up shot of SUD junior police officer in a brown Delhi Police uniform adorned with badges, insignia, and a police cap, speaking with focus and determination to the senior officer. Behind him, the white Delhi Police patrol vehicle with red and blue flashing lights is visible, creating a striking backdrop. The posh bar hotel with vibrant lights and luxury cars adds depth in the softly blurred midnight background, enhancing the cinematic tone with HDR quality", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 2.11, "output_quality": 80, "prompt_strength": 0.83, "extra_lora_scale": 1, "num_inference_steps": 28 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run kondagen/flux-char-sud using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "kondagen/flux-char-sud:5600053d00273b453cd1edaf71d7e7dc8b02cac3d243be1d3f51d2a734f2d00f", { input: { model: "dev", prompt: " Medium close-up shot of SUD junior police officer in a brown Delhi Police uniform adorned with badges, insignia, and a police cap, speaking with focus and determination to the senior officer. Behind him, the white Delhi Police patrol vehicle with red and blue flashing lights is visible, creating a striking backdrop. The posh bar hotel with vibrant lights and luxury cars adds depth in the softly blurred midnight background, enhancing the cinematic tone with HDR quality", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "16:9", output_format: "jpg", guidance_scale: 2.11, output_quality: 80, prompt_strength: 0.83, 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.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run kondagen/flux-char-sud using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "kondagen/flux-char-sud:5600053d00273b453cd1edaf71d7e7dc8b02cac3d243be1d3f51d2a734f2d00f", input={ "model": "dev", "prompt": " Medium close-up shot of SUD junior police officer in a brown Delhi Police uniform adorned with badges, insignia, and a police cap, speaking with focus and determination to the senior officer. Behind him, the white Delhi Police patrol vehicle with red and blue flashing lights is visible, creating a striking backdrop. The posh bar hotel with vibrant lights and luxury cars adds depth in the softly blurred midnight background, enhancing the cinematic tone with HDR quality", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 2.11, "output_quality": 80, "prompt_strength": 0.83, "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_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run kondagen/flux-char-sud 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": "5600053d00273b453cd1edaf71d7e7dc8b02cac3d243be1d3f51d2a734f2d00f", "input": { "model": "dev", "prompt": " Medium close-up shot of SUD junior police officer in a brown Delhi Police uniform adorned with badges, insignia, and a police cap, speaking with focus and determination to the senior officer. Behind him, the white Delhi Police patrol vehicle with red and blue flashing lights is visible, creating a striking backdrop. The posh bar hotel with vibrant lights and luxury cars adds depth in the softly blurred midnight background, enhancing the cinematic tone with HDR quality", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 2.11, "output_quality": 80, "prompt_strength": 0.83, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run kondagen/flux-char-sud using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/kondagen/flux-char-sud@sha256:5600053d00273b453cd1edaf71d7e7dc8b02cac3d243be1d3f51d2a734f2d00f \ -i 'model="dev"' \ -i 'prompt=" Medium close-up shot of SUD junior police officer in a brown Delhi Police uniform adorned with badges, insignia, and a police cap, speaking with focus and determination to the senior officer. Behind him, the white Delhi Police patrol vehicle with red and blue flashing lights is visible, creating a striking backdrop. The posh bar hotel with vibrant lights and luxury cars adds depth in the softly blurred midnight background, enhancing the cinematic tone with HDR quality"' \ -i 'go_fast=false' \ -i 'lora_scale=1' \ -i 'megapixels="1"' \ -i 'num_outputs=1' \ -i 'aspect_ratio="16:9"' \ -i 'output_format="jpg"' \ -i 'guidance_scale=2.11' \ -i 'output_quality=80' \ -i 'prompt_strength=0.83' \ -i 'extra_lora_scale=1' \ -i 'num_inference_steps=28'
To learn more, take a look at the Cog documentation.
Pull and run kondagen/flux-char-sud using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/kondagen/flux-char-sud@sha256:5600053d00273b453cd1edaf71d7e7dc8b02cac3d243be1d3f51d2a734f2d00f
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "model": "dev", "prompt": " Medium close-up shot of SUD junior police officer in a brown Delhi Police uniform adorned with badges, insignia, and a police cap, speaking with focus and determination to the senior officer. Behind him, the white Delhi Police patrol vehicle with red and blue flashing lights is visible, creating a striking backdrop. The posh bar hotel with vibrant lights and luxury cars adds depth in the softly blurred midnight background, enhancing the cinematic tone with HDR quality", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 2.11, "output_quality": 80, "prompt_strength": 0.83, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ http://localhost:5000/predictions
Output
{ "completed_at": "2025-02-02T15:16:10.890306Z", "created_at": "2025-02-02T15:15:58.560000Z", "data_removed": false, "error": null, "id": "fmn0p9mnw1rma0cmrwxtnt9b9w", "input": { "model": "dev", "prompt": " Medium close-up shot of SUD junior police officer in a brown Delhi Police uniform adorned with badges, insignia, and a police cap, speaking with focus and determination to the senior officer. Behind him, the white Delhi Police patrol vehicle with red and blue flashing lights is visible, creating a striking backdrop. The posh bar hotel with vibrant lights and luxury cars adds depth in the softly blurred midnight background, enhancing the cinematic tone with HDR quality", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 2.11, "output_quality": 80, "prompt_strength": 0.83, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2025-02-02 15:16:02.437 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-02-02 15:16:02.437 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2731.43it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2576.06it/s]\n2025-02-02 15:16:02.556 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s\nfree=28727033651200\nDownloading weights\n2025-02-02T15:16:02Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpv69os2eo/weights url=https://replicate.delivery/xezq/EJZkQB4ZqKZTFFpKFumV2QgWQjLXaIlmbUPHx9oIXZdexoFKA/trained_model.tar\n2025-02-02T15:16:04Z | INFO | [ Complete ] dest=/tmp/tmpv69os2eo/weights size=\"172 MB\" total_elapsed=2.163s url=https://replicate.delivery/xezq/EJZkQB4ZqKZTFFpKFumV2QgWQjLXaIlmbUPHx9oIXZdexoFKA/trained_model.tar\nDownloaded weights in 2.19s\n2025-02-02 15:16:04.745 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/91009f4a9f83aae4\n2025-02-02 15:16:04.816 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-02-02 15:16:04.817 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-02-02 15:16:04.817 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2736.06it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2579.81it/s]\n2025-02-02 15:16:04.935 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s\nUsing seed: 58714\n0it [00:00, ?it/s]\n1it [00:00, 8.42it/s]\n2it [00:00, 5.91it/s]\n3it [00:00, 5.39it/s]\n4it [00:00, 5.17it/s]\n5it [00:00, 5.06it/s]\n6it [00:01, 5.00it/s]\n7it [00:01, 4.96it/s]\n8it [00:01, 4.92it/s]\n9it [00:01, 4.91it/s]\n10it [00:01, 4.90it/s]\n11it [00:02, 4.89it/s]\n12it [00:02, 4.88it/s]\n13it [00:02, 4.88it/s]\n14it [00:02, 4.88it/s]\n15it [00:02, 4.88it/s]\n16it [00:03, 4.88it/s]\n17it [00:03, 4.87it/s]\n18it [00:03, 4.87it/s]\n19it [00:03, 4.87it/s]\n20it [00:04, 4.88it/s]\n21it [00:04, 4.88it/s]\n22it [00:04, 4.88it/s]\n23it [00:04, 4.88it/s]\n24it [00:04, 4.88it/s]\n25it [00:05, 4.88it/s]\n26it [00:05, 4.88it/s]\n27it [00:05, 4.88it/s]\n28it [00:05, 4.88it/s]\n28it [00:05, 4.95it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 8.452946101, "total_time": 12.330306 }, "output": [ "https://replicate.delivery/xezq/jyufQhfG3OndFUam8xf4LfBL6bwgdsmxRe7renwKTfxcd8pFKA/out-0.jpg" ], "started_at": "2025-02-02T15:16:02.437360Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bsvm-t7m3pl47j63numx65sgagwpcnadj3ikmypfmfckxhfl2j5ydjcra", "get": "https://api.replicate.com/v1/predictions/fmn0p9mnw1rma0cmrwxtnt9b9w", "cancel": "https://api.replicate.com/v1/predictions/fmn0p9mnw1rma0cmrwxtnt9b9w/cancel" }, "version": "5600053d00273b453cd1edaf71d7e7dc8b02cac3d243be1d3f51d2a734f2d00f" }
Generated in2025-02-02 15:16:02.437 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-02-02 15:16:02.437 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2731.43it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2576.06it/s] 2025-02-02 15:16:02.556 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s free=28727033651200 Downloading weights 2025-02-02T15:16:02Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpv69os2eo/weights url=https://replicate.delivery/xezq/EJZkQB4ZqKZTFFpKFumV2QgWQjLXaIlmbUPHx9oIXZdexoFKA/trained_model.tar 2025-02-02T15:16:04Z | INFO | [ Complete ] dest=/tmp/tmpv69os2eo/weights size="172 MB" total_elapsed=2.163s url=https://replicate.delivery/xezq/EJZkQB4ZqKZTFFpKFumV2QgWQjLXaIlmbUPHx9oIXZdexoFKA/trained_model.tar Downloaded weights in 2.19s 2025-02-02 15:16:04.745 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/91009f4a9f83aae4 2025-02-02 15:16:04.816 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-02-02 15:16:04.817 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-02-02 15:16:04.817 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2736.06it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2579.81it/s] 2025-02-02 15:16:04.935 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s Using seed: 58714 0it [00:00, ?it/s] 1it [00:00, 8.42it/s] 2it [00:00, 5.91it/s] 3it [00:00, 5.39it/s] 4it [00:00, 5.17it/s] 5it [00:00, 5.06it/s] 6it [00:01, 5.00it/s] 7it [00:01, 4.96it/s] 8it [00:01, 4.92it/s] 9it [00:01, 4.91it/s] 10it [00:01, 4.90it/s] 11it [00:02, 4.89it/s] 12it [00:02, 4.88it/s] 13it [00:02, 4.88it/s] 14it [00:02, 4.88it/s] 15it [00:02, 4.88it/s] 16it [00:03, 4.88it/s] 17it [00:03, 4.87it/s] 18it [00:03, 4.87it/s] 19it [00:03, 4.87it/s] 20it [00:04, 4.88it/s] 21it [00:04, 4.88it/s] 22it [00:04, 4.88it/s] 23it [00:04, 4.88it/s] 24it [00:04, 4.88it/s] 25it [00:05, 4.88it/s] 26it [00:05, 4.88it/s] 27it [00:05, 4.88it/s] 28it [00:05, 4.88it/s] 28it [00:05, 4.95it/s] Total safe images: 1 out of 1
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