authbyte / flux-funko-pop
Generates in the style of a Funko Pop
- Public
- 205 runs
-
H100
Prediction
authbyte/flux-funko-pop:5bf170ccf18c3fb0ae11b4232c8f45a793ba2c4b6f19f825b9cb336bbb652655IDmc48ps91gxrmc0cm1zd8emd9jrStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- FUNKO of a woman dressed in a suit
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "FUNKO of a woman dressed in a suit", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run authbyte/flux-funko-pop using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "authbyte/flux-funko-pop:5bf170ccf18c3fb0ae11b4232c8f45a793ba2c4b6f19f825b9cb336bbb652655", { input: { model: "dev", prompt: "FUNKO of a woman dressed in a suit", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3, output_quality: 80, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun authbyte/flux-funko-pop using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "authbyte/flux-funko-pop:5bf170ccf18c3fb0ae11b4232c8f45a793ba2c4b6f19f825b9cb336bbb652655", input={ "model": "dev", "prompt": "FUNKO of a woman dressed in a suit", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run authbyte/flux-funko-pop 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": "authbyte/flux-funko-pop:5bf170ccf18c3fb0ae11b4232c8f45a793ba2c4b6f19f825b9cb336bbb652655", "input": { "model": "dev", "prompt": "FUNKO of a woman dressed in a suit", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-12-29T00:39:07.834838Z", "created_at": "2024-12-29T00:39:01.255000Z", "data_removed": false, "error": null, "id": "mc48ps91gxrmc0cm1zd8emd9jr", "input": { "model": "dev", "prompt": "FUNKO of a woman dressed in a suit", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2024-12-29 00:39:01.421 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2024-12-29 00:39:01.422 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 93%|█████████▎| 283/304 [00:00<00:00, 2827.72it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2742.25it/s]\n2024-12-29 00:39:01.533 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s\n2024-12-29 00:39:01.534 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/a0dc7bb4c4fc7909\n2024-12-29 00:39:01.655 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2024-12-29 00:39:01.655 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2024-12-29 00:39:01.655 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 93%|█████████▎| 284/304 [00:00<00:00, 2827.46it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2745.28it/s]\n2024-12-29 00:39:01.766 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s\nUsing seed: 19160\n0it [00:00, ?it/s]\n1it [00:00, 8.37it/s]\n2it [00:00, 5.86it/s]\n3it [00:00, 5.34it/s]\n4it [00:00, 5.13it/s]\n5it [00:00, 5.01it/s]\n6it [00:01, 4.92it/s]\n7it [00:01, 4.88it/s]\n8it [00:01, 4.87it/s]\n9it [00:01, 4.87it/s]\n10it [00:01, 4.85it/s]\n11it [00:02, 4.84it/s]\n12it [00:02, 4.84it/s]\n13it [00:02, 4.83it/s]\n14it [00:02, 4.83it/s]\n15it [00:03, 4.83it/s]\n16it [00:03, 4.82it/s]\n17it [00:03, 4.81it/s]\n18it [00:03, 4.81it/s]\n19it [00:03, 4.81it/s]\n20it [00:04, 4.81it/s]\n21it [00:04, 4.81it/s]\n22it [00:04, 4.81it/s]\n23it [00:04, 4.81it/s]\n24it [00:04, 4.81it/s]\n25it [00:05, 4.81it/s]\n26it [00:05, 4.82it/s]\n27it [00:05, 4.81it/s]\n28it [00:05, 4.81it/s]\n28it [00:05, 4.89it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 6.412236085, "total_time": 6.579838 }, "output": [ "https://replicate.delivery/xezq/oQs4dSpfhu3GH6xw7tq3DDfqTMzJQe8tZrNdUJTtzibWhJfPB/out-0.webp" ], "started_at": "2024-12-29T00:39:01.422602Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-c2lkx7spiypyqhcuiqoyoutonbwdij6lc7ixvf7xasjizqylqzxa", "get": "https://api.replicate.com/v1/predictions/mc48ps91gxrmc0cm1zd8emd9jr", "cancel": "https://api.replicate.com/v1/predictions/mc48ps91gxrmc0cm1zd8emd9jr/cancel" }, "version": "5bf170ccf18c3fb0ae11b4232c8f45a793ba2c4b6f19f825b9cb336bbb652655" }Generated in2024-12-29 00:39:01.421 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2024-12-29 00:39:01.422 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 93%|█████████▎| 283/304 [00:00<00:00, 2827.72it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2742.25it/s] 2024-12-29 00:39:01.533 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s 2024-12-29 00:39:01.534 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/a0dc7bb4c4fc7909 2024-12-29 00:39:01.655 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2024-12-29 00:39:01.655 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2024-12-29 00:39:01.655 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 93%|█████████▎| 284/304 [00:00<00:00, 2827.46it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2745.28it/s] 2024-12-29 00:39:01.766 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s Using seed: 19160 0it [00:00, ?it/s] 1it [00:00, 8.37it/s] 2it [00:00, 5.86it/s] 3it [00:00, 5.34it/s] 4it [00:00, 5.13it/s] 5it [00:00, 5.01it/s] 6it [00:01, 4.92it/s] 7it [00:01, 4.88it/s] 8it [00:01, 4.87it/s] 9it [00:01, 4.87it/s] 10it [00:01, 4.85it/s] 11it [00:02, 4.84it/s] 12it [00:02, 4.84it/s] 13it [00:02, 4.83it/s] 14it [00:02, 4.83it/s] 15it [00:03, 4.83it/s] 16it [00:03, 4.82it/s] 17it [00:03, 4.81it/s] 18it [00:03, 4.81it/s] 19it [00:03, 4.81it/s] 20it [00:04, 4.81it/s] 21it [00:04, 4.81it/s] 22it [00:04, 4.81it/s] 23it [00:04, 4.81it/s] 24it [00:04, 4.81it/s] 25it [00:05, 4.81it/s] 26it [00:05, 4.82it/s] 27it [00:05, 4.81it/s] 28it [00:05, 4.81it/s] 28it [00:05, 4.89it/s] Total safe images: 1 out of 1Prediction
authbyte/flux-funko-pop:5bf170ccf18c3fb0ae11b4232c8f45a793ba2c4b6f19f825b9cb336bbb652655ID86t932x8esrme0cm1zc92b440rStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- FUNKO pop of Elon Musk
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "FUNKO pop of Elon Musk", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run authbyte/flux-funko-pop using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "authbyte/flux-funko-pop:5bf170ccf18c3fb0ae11b4232c8f45a793ba2c4b6f19f825b9cb336bbb652655", { input: { model: "dev", prompt: "FUNKO pop of Elon Musk", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3, output_quality: 80, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun authbyte/flux-funko-pop using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "authbyte/flux-funko-pop:5bf170ccf18c3fb0ae11b4232c8f45a793ba2c4b6f19f825b9cb336bbb652655", input={ "model": "dev", "prompt": "FUNKO pop of Elon Musk", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run authbyte/flux-funko-pop 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": "authbyte/flux-funko-pop:5bf170ccf18c3fb0ae11b4232c8f45a793ba2c4b6f19f825b9cb336bbb652655", "input": { "model": "dev", "prompt": "FUNKO pop of Elon Musk", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-12-29T00:37:35.031743Z", "created_at": "2024-12-29T00:37:24.726000Z", "data_removed": false, "error": null, "id": "86t932x8esrme0cm1zc92b440r", "input": { "model": "dev", "prompt": "FUNKO pop of Elon Musk", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2024-12-29 00:37:27.253 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2024-12-29 00:37:27.253 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 94%|█████████▍| 287/304 [00:00<00:00, 2862.33it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2690.92it/s]\n2024-12-29 00:37:27.366 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s\nfree=29946337783808\nDownloading weights\n2024-12-29T00:37:27Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpdo8acm6t/weights url=https://replicate.delivery/xezq/l6YoVVImEJ4YK9Bj3vP2GGLMKA1Pa9CrzfE70Fn5fXjtukfnA/trained_model.tar\n2024-12-29T00:37:28Z | INFO | [ Complete ] dest=/tmp/tmpdo8acm6t/weights size=\"172 MB\" total_elapsed=1.367s url=https://replicate.delivery/xezq/l6YoVVImEJ4YK9Bj3vP2GGLMKA1Pa9CrzfE70Fn5fXjtukfnA/trained_model.tar\nDownloaded weights in 1.39s\n2024-12-29 00:37:28.758 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/a0dc7bb4c4fc7909\n2024-12-29 00:37:28.828 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2024-12-29 00:37:28.828 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2024-12-29 00:37:28.828 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 94%|█████████▍| 287/304 [00:00<00:00, 2867.66it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2695.60it/s]\n2024-12-29 00:37:28.941 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.18s\nUsing seed: 58125\n0it [00:00, ?it/s]\n1it [00:00, 8.41it/s]\n2it [00:00, 5.89it/s]\n3it [00:00, 5.36it/s]\n4it [00:00, 5.15it/s]\n5it [00:00, 5.00it/s]\n6it [00:01, 4.92it/s]\n7it [00:01, 4.88it/s]\n8it [00:01, 4.87it/s]\n9it [00:01, 4.86it/s]\n10it [00:01, 4.83it/s]\n11it [00:02, 4.81it/s]\n12it [00:02, 4.80it/s]\n13it [00:02, 4.81it/s]\n14it [00:02, 4.82it/s]\n15it [00:03, 4.81it/s]\n16it [00:03, 4.78it/s]\n17it [00:03, 4.79it/s]\n18it [00:03, 4.79it/s]\n19it [00:03, 4.80it/s]\n20it [00:04, 4.80it/s]\n21it [00:04, 4.79it/s]\n22it [00:04, 4.79it/s]\n23it [00:04, 4.79it/s]\n24it [00:04, 4.79it/s]\n25it [00:05, 4.79it/s]\n26it [00:05, 4.78it/s]\n27it [00:05, 4.79it/s]\n28it [00:05, 4.79it/s]\n28it [00:05, 4.87it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 7.777757184, "total_time": 10.305743 }, "output": [ "https://replicate.delivery/xezq/pVxPEKtpPTLeNim0zp87QsZnNbXHG912WXqMvq939OunXyfTA/out-0.webp" ], "started_at": "2024-12-29T00:37:27.253986Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-2end2ccrtrl33gdggjga3ovrs3ztpdlqe7chbxaguknmwalvafpa", "get": "https://api.replicate.com/v1/predictions/86t932x8esrme0cm1zc92b440r", "cancel": "https://api.replicate.com/v1/predictions/86t932x8esrme0cm1zc92b440r/cancel" }, "version": "5bf170ccf18c3fb0ae11b4232c8f45a793ba2c4b6f19f825b9cb336bbb652655" }Generated in2024-12-29 00:37:27.253 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2024-12-29 00:37:27.253 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 94%|█████████▍| 287/304 [00:00<00:00, 2862.33it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2690.92it/s] 2024-12-29 00:37:27.366 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s free=29946337783808 Downloading weights 2024-12-29T00:37:27Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpdo8acm6t/weights url=https://replicate.delivery/xezq/l6YoVVImEJ4YK9Bj3vP2GGLMKA1Pa9CrzfE70Fn5fXjtukfnA/trained_model.tar 2024-12-29T00:37:28Z | INFO | [ Complete ] dest=/tmp/tmpdo8acm6t/weights size="172 MB" total_elapsed=1.367s url=https://replicate.delivery/xezq/l6YoVVImEJ4YK9Bj3vP2GGLMKA1Pa9CrzfE70Fn5fXjtukfnA/trained_model.tar Downloaded weights in 1.39s 2024-12-29 00:37:28.758 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/a0dc7bb4c4fc7909 2024-12-29 00:37:28.828 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2024-12-29 00:37:28.828 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2024-12-29 00:37:28.828 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 94%|█████████▍| 287/304 [00:00<00:00, 2867.66it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2695.60it/s] 2024-12-29 00:37:28.941 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.18s Using seed: 58125 0it [00:00, ?it/s] 1it [00:00, 8.41it/s] 2it [00:00, 5.89it/s] 3it [00:00, 5.36it/s] 4it [00:00, 5.15it/s] 5it [00:00, 5.00it/s] 6it [00:01, 4.92it/s] 7it [00:01, 4.88it/s] 8it [00:01, 4.87it/s] 9it [00:01, 4.86it/s] 10it [00:01, 4.83it/s] 11it [00:02, 4.81it/s] 12it [00:02, 4.80it/s] 13it [00:02, 4.81it/s] 14it [00:02, 4.82it/s] 15it [00:03, 4.81it/s] 16it [00:03, 4.78it/s] 17it [00:03, 4.79it/s] 18it [00:03, 4.79it/s] 19it [00:03, 4.80it/s] 20it [00:04, 4.80it/s] 21it [00:04, 4.79it/s] 22it [00:04, 4.79it/s] 23it [00:04, 4.79it/s] 24it [00:04, 4.79it/s] 25it [00:05, 4.79it/s] 26it [00:05, 4.78it/s] 27it [00:05, 4.79it/s] 28it [00:05, 4.79it/s] 28it [00:05, 4.87it/s] Total safe images: 1 out of 1
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