Flux lora, use "MNCRFTMOV" to trigger image generation
- Public
- 6.6K runs
-
H100
- Paper
Prediction
fofr/flux-minecraft-movie:23cd3151875f9caf78b022d9409425d04e3a5b0fa093d07590b37d3f98fef682IDc581j24srsrm20chrbg8eebqjrStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a MNCRFTMOV film render of a blocky weird toad, minecraft style
- lora_scale
- 1
- num_outputs
- 4
- 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 MNCRFTMOV film render of a blocky weird toad, minecraft style", "lora_scale": 1, "num_outputs": 4, "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 replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/flux-minecraft-movie using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-minecraft-movie:23cd3151875f9caf78b022d9409425d04e3a5b0fa093d07590b37d3f98fef682", { input: { model: "dev", prompt: "a MNCRFTMOV film render of a blocky weird toad, minecraft style", lora_scale: 1, num_outputs: 4, 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 } } ); // 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 fofr/flux-minecraft-movie using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-minecraft-movie:23cd3151875f9caf78b022d9409425d04e3a5b0fa093d07590b37d3f98fef682", input={ "model": "dev", "prompt": "a MNCRFTMOV film render of a blocky weird toad, minecraft style", "lora_scale": 1, "num_outputs": 4, "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.
Run fofr/flux-minecraft-movie 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": "fofr/flux-minecraft-movie:23cd3151875f9caf78b022d9409425d04e3a5b0fa093d07590b37d3f98fef682", "input": { "model": "dev", "prompt": "a MNCRFTMOV film render of a blocky weird toad, minecraft style", "lora_scale": 1, "num_outputs": 4, "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": "2024-09-05T15:53:47.695764Z", "created_at": "2024-09-05T15:49:45.030000Z", "data_removed": false, "error": null, "id": "c581j24srsrm20chrbg8eebqjr", "input": { "model": "dev", "prompt": "a MNCRFTMOV film render of a blocky weird toad, minecraft style", "lora_scale": 1, "num_outputs": 4, "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: 32949\nPrompt: a MNCRFTMOV film render of a blocky weird toad, minecraft style\ntxt2img mode\nUsing dev model\nfree=8553165783040\nDownloading weights\n2024-09-05T15:53:04Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpaac46e5m/weights url=https://replicate.delivery/yhqm/BW3MClLgrapLDdbEgeKmqt3uvhGibk9ldxVNr6DWNoeW90ZTA/trained_model.tar\n2024-09-05T15:53:07Z | INFO | [ Complete ] dest=/tmp/tmpaac46e5m/weights size=\"172 MB\" total_elapsed=2.013s url=https://replicate.delivery/yhqm/BW3MClLgrapLDdbEgeKmqt3uvhGibk9ldxVNr6DWNoeW90ZTA/trained_model.tar\nDownloaded weights in 2.11s\nLoaded LoRAs in 11.14s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:28, 1.07s/it]\n 7%|▋ | 2/28 [00:01<00:24, 1.05it/s]\n 11%|█ | 3/28 [00:03<00:25, 1.01s/it]\n 14%|█▍ | 4/28 [00:04<00:24, 1.03s/it]\n 18%|█▊ | 5/28 [00:05<00:24, 1.05s/it]\n 21%|██▏ | 6/28 [00:06<00:23, 1.06s/it]\n 25%|██▌ | 7/28 [00:07<00:22, 1.06s/it]\n 29%|██▊ | 8/28 [00:08<00:21, 1.07s/it]\n 32%|███▏ | 9/28 [00:09<00:20, 1.07s/it]\n 36%|███▌ | 10/28 [00:10<00:19, 1.07s/it]\n 39%|███▉ | 11/28 [00:11<00:18, 1.08s/it]\n 43%|████▎ | 12/28 [00:12<00:17, 1.08s/it]\n 46%|████▋ | 13/28 [00:13<00:16, 1.08s/it]\n 50%|█████ | 14/28 [00:14<00:15, 1.08s/it]\n 54%|█████▎ | 15/28 [00:15<00:14, 1.08s/it]\n 57%|█████▋ | 16/28 [00:17<00:12, 1.08s/it]\n 61%|██████ | 17/28 [00:18<00:11, 1.08s/it]\n 64%|██████▍ | 18/28 [00:19<00:10, 1.07s/it]\n 68%|██████▊ | 19/28 [00:20<00:09, 1.08s/it]\n 71%|███████▏ | 20/28 [00:21<00:08, 1.08s/it]\n 75%|███████▌ | 21/28 [00:22<00:07, 1.08s/it]\n 79%|███████▊ | 22/28 [00:23<00:06, 1.08s/it]\n 82%|████████▏ | 23/28 [00:24<00:05, 1.07s/it]\n 86%|████████▌ | 24/28 [00:25<00:04, 1.08s/it]\n 89%|████████▉ | 25/28 [00:26<00:03, 1.07s/it]\n 93%|█████████▎| 26/28 [00:27<00:02, 1.07s/it]\n 96%|█████████▋| 27/28 [00:28<00:01, 1.07s/it]\n100%|██████████| 28/28 [00:29<00:00, 1.07s/it]\n100%|██████████| 28/28 [00:29<00:00, 1.07s/it]", "metrics": { "predict_time": 42.782051329, "total_time": 242.665764 }, "output": [ "https://replicate.delivery/yhqm/awL4K5AsM0baFRHOm1Z9FMr9xBXIYgfTHz4ubt6xfYTLY4ZTA/out-0.webp", "https://replicate.delivery/yhqm/Hfwjtw0A7aVHPaFcjO7BKWJaqrrCgrLzjIi77esdgvFLY4ZTA/out-1.webp", "https://replicate.delivery/yhqm/Kuiftlufhvq0NklfRCZEqdgdVNt3pfeqv10HYmT5KiEcBDPbC/out-2.webp", "https://replicate.delivery/yhqm/gq0PyMWOQSZVGxc1czBDv7edquOtJ723hfvX08fpearsghnNB/out-3.webp" ], "started_at": "2024-09-05T15:53:04.913713Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/c581j24srsrm20chrbg8eebqjr", "cancel": "https://api.replicate.com/v1/predictions/c581j24srsrm20chrbg8eebqjr/cancel" }, "version": "23cd3151875f9caf78b022d9409425d04e3a5b0fa093d07590b37d3f98fef682" }Generated inUsing seed: 32949 Prompt: a MNCRFTMOV film render of a blocky weird toad, minecraft style txt2img mode Using dev model free=8553165783040 Downloading weights 2024-09-05T15:53:04Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpaac46e5m/weights url=https://replicate.delivery/yhqm/BW3MClLgrapLDdbEgeKmqt3uvhGibk9ldxVNr6DWNoeW90ZTA/trained_model.tar 2024-09-05T15:53:07Z | INFO | [ Complete ] dest=/tmp/tmpaac46e5m/weights size="172 MB" total_elapsed=2.013s url=https://replicate.delivery/yhqm/BW3MClLgrapLDdbEgeKmqt3uvhGibk9ldxVNr6DWNoeW90ZTA/trained_model.tar Downloaded weights in 2.11s Loaded LoRAs in 11.14s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:28, 1.07s/it] 7%|▋ | 2/28 [00:01<00:24, 1.05it/s] 11%|█ | 3/28 [00:03<00:25, 1.01s/it] 14%|█▍ | 4/28 [00:04<00:24, 1.03s/it] 18%|█▊ | 5/28 [00:05<00:24, 1.05s/it] 21%|██▏ | 6/28 [00:06<00:23, 1.06s/it] 25%|██▌ | 7/28 [00:07<00:22, 1.06s/it] 29%|██▊ | 8/28 [00:08<00:21, 1.07s/it] 32%|███▏ | 9/28 [00:09<00:20, 1.07s/it] 36%|███▌ | 10/28 [00:10<00:19, 1.07s/it] 39%|███▉ | 11/28 [00:11<00:18, 1.08s/it] 43%|████▎ | 12/28 [00:12<00:17, 1.08s/it] 46%|████▋ | 13/28 [00:13<00:16, 1.08s/it] 50%|█████ | 14/28 [00:14<00:15, 1.08s/it] 54%|█████▎ | 15/28 [00:15<00:14, 1.08s/it] 57%|█████▋ | 16/28 [00:17<00:12, 1.08s/it] 61%|██████ | 17/28 [00:18<00:11, 1.08s/it] 64%|██████▍ | 18/28 [00:19<00:10, 1.07s/it] 68%|██████▊ | 19/28 [00:20<00:09, 1.08s/it] 71%|███████▏ | 20/28 [00:21<00:08, 1.08s/it] 75%|███████▌ | 21/28 [00:22<00:07, 1.08s/it] 79%|███████▊ | 22/28 [00:23<00:06, 1.08s/it] 82%|████████▏ | 23/28 [00:24<00:05, 1.07s/it] 86%|████████▌ | 24/28 [00:25<00:04, 1.08s/it] 89%|████████▉ | 25/28 [00:26<00:03, 1.07s/it] 93%|█████████▎| 26/28 [00:27<00:02, 1.07s/it] 96%|█████████▋| 27/28 [00:28<00:01, 1.07s/it] 100%|██████████| 28/28 [00:29<00:00, 1.07s/it] 100%|██████████| 28/28 [00:29<00:00, 1.07s/it]Prediction
fofr/flux-minecraft-movie:23cd3151875f9caf78b022d9409425d04e3a5b0fa093d07590b37d3f98fef682IDe969w4x395rm20chr88sx8b36cStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a MNCRFTMOV film render of a goofy blocky tiger
- 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 MNCRFTMOV film render of a goofy blocky tiger", "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 replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/flux-minecraft-movie using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-minecraft-movie:23cd3151875f9caf78b022d9409425d04e3a5b0fa093d07590b37d3f98fef682", { input: { model: "dev", prompt: "a MNCRFTMOV film render of a goofy blocky tiger", 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 } } ); // 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 fofr/flux-minecraft-movie using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-minecraft-movie:23cd3151875f9caf78b022d9409425d04e3a5b0fa093d07590b37d3f98fef682", input={ "model": "dev", "prompt": "a MNCRFTMOV film render of a goofy blocky tiger", "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.
Run fofr/flux-minecraft-movie 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": "fofr/flux-minecraft-movie:23cd3151875f9caf78b022d9409425d04e3a5b0fa093d07590b37d3f98fef682", "input": { "model": "dev", "prompt": "a MNCRFTMOV film render of a goofy blocky tiger", "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": "2024-09-05T12:04:03.236733Z", "created_at": "2024-09-05T12:03:41.513000Z", "data_removed": false, "error": null, "id": "e969w4x395rm20chr88sx8b36c", "input": { "model": "dev", "prompt": "a MNCRFTMOV film render of a goofy blocky tiger", "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: 10241\nPrompt: a MNCRFTMOV film render of a goofy blocky tiger\ntxt2img mode\nUsing dev model\nfree=8414057836544\nDownloading weights\n2024-09-05T12:03:41Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpso81ouey/weights url=https://replicate.delivery/yhqm/BW3MClLgrapLDdbEgeKmqt3uvhGibk9ldxVNr6DWNoeW90ZTA/trained_model.tar\n2024-09-05T12:03:44Z | INFO | [ Complete ] dest=/tmp/tmpso81ouey/weights size=\"172 MB\" total_elapsed=3.235s url=https://replicate.delivery/yhqm/BW3MClLgrapLDdbEgeKmqt3uvhGibk9ldxVNr6DWNoeW90ZTA/trained_model.tar\nDownloaded weights in 3.26s\nLoaded LoRAs in 13.17s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.48it/s]\n 7%|▋ | 2/28 [00:00<00:06, 3.94it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.71it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.62it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.57it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.54it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.52it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.51it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.50it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.50it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.49it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.49it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.49it/s]\n 50%|█████ | 14/28 [00:03<00:04, 3.49it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.49it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.48it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.48it/s]\n 64%|██████▍ | 18/28 [00:05<00:02, 3.48it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.48it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.48it/s]\n 75%|███████▌ | 21/28 [00:05<00:02, 3.48it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.48it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.49it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.49it/s]\n 89%|████████▉ | 25/28 [00:07<00:00, 3.49it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.48it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.49it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.48it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.51it/s]", "metrics": { "predict_time": 21.717234544, "total_time": 21.723733 }, "output": [ "https://replicate.delivery/yhqm/SRbLbSvEOWIlGR3vvMvENRiCg7sGweEaLLETxUs5yT4Zg6sJA/out-0.webp" ], "started_at": "2024-09-05T12:03:41.519499Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/e969w4x395rm20chr88sx8b36c", "cancel": "https://api.replicate.com/v1/predictions/e969w4x395rm20chr88sx8b36c/cancel" }, "version": "23cd3151875f9caf78b022d9409425d04e3a5b0fa093d07590b37d3f98fef682" }Generated inUsing seed: 10241 Prompt: a MNCRFTMOV film render of a goofy blocky tiger txt2img mode Using dev model free=8414057836544 Downloading weights 2024-09-05T12:03:41Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpso81ouey/weights url=https://replicate.delivery/yhqm/BW3MClLgrapLDdbEgeKmqt3uvhGibk9ldxVNr6DWNoeW90ZTA/trained_model.tar 2024-09-05T12:03:44Z | INFO | [ Complete ] dest=/tmp/tmpso81ouey/weights size="172 MB" total_elapsed=3.235s url=https://replicate.delivery/yhqm/BW3MClLgrapLDdbEgeKmqt3uvhGibk9ldxVNr6DWNoeW90ZTA/trained_model.tar Downloaded weights in 3.26s Loaded LoRAs in 13.17s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.48it/s] 7%|▋ | 2/28 [00:00<00:06, 3.94it/s] 11%|█ | 3/28 [00:00<00:06, 3.71it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.62it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.57it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.54it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.52it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.51it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.50it/s] 36%|███▌ | 10/28 [00:02<00:05, 3.50it/s] 39%|███▉ | 11/28 [00:03<00:04, 3.49it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.49it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.49it/s] 50%|█████ | 14/28 [00:03<00:04, 3.49it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.49it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.48it/s] 61%|██████ | 17/28 [00:04<00:03, 3.48it/s] 64%|██████▍ | 18/28 [00:05<00:02, 3.48it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.48it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.48it/s] 75%|███████▌ | 21/28 [00:05<00:02, 3.48it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.48it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.49it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.49it/s] 89%|████████▉ | 25/28 [00:07<00:00, 3.49it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.48it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.49it/s] 100%|██████████| 28/28 [00:07<00:00, 3.48it/s] 100%|██████████| 28/28 [00:07<00:00, 3.51it/s]Prediction
fofr/flux-minecraft-movie:23cd3151875f9caf78b022d9409425d04e3a5b0fa093d07590b37d3f98fef682IDed1q74thhdrm60chr9qt0ra05wStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a MNCRFTMOV film render of a goofy blocky tiger
- 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 MNCRFTMOV film render of a goofy blocky tiger", "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 replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/flux-minecraft-movie using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-minecraft-movie:23cd3151875f9caf78b022d9409425d04e3a5b0fa093d07590b37d3f98fef682", { input: { model: "dev", prompt: "a MNCRFTMOV film render of a goofy blocky tiger", 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 } } ); // 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 fofr/flux-minecraft-movie using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-minecraft-movie:23cd3151875f9caf78b022d9409425d04e3a5b0fa093d07590b37d3f98fef682", input={ "model": "dev", "prompt": "a MNCRFTMOV film render of a goofy blocky tiger", "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.
Run fofr/flux-minecraft-movie 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": "fofr/flux-minecraft-movie:23cd3151875f9caf78b022d9409425d04e3a5b0fa093d07590b37d3f98fef682", "input": { "model": "dev", "prompt": "a MNCRFTMOV film render of a goofy blocky tiger", "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": "2024-09-05T13:46:23.455970Z", "created_at": "2024-09-05T13:46:00.971000Z", "data_removed": false, "error": null, "id": "ed1q74thhdrm60chr9qt0ra05w", "input": { "model": "dev", "prompt": "a MNCRFTMOV film render of a goofy blocky tiger", "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: 7564\nPrompt: a MNCRFTMOV film render of a goofy blocky tiger\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 7.99s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.47it/s]\n 7%|▋ | 2/28 [00:00<00:06, 3.93it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.71it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.61it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.56it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.53it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.51it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.50it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.49it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.48it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.48it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.48it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.47it/s]\n 50%|█████ | 14/28 [00:03<00:04, 3.47it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.47it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.47it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.47it/s]\n 64%|██████▍ | 18/28 [00:05<00:02, 3.47it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.47it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.47it/s]\n 75%|███████▌ | 21/28 [00:05<00:02, 3.47it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.47it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.47it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.47it/s]\n 89%|████████▉ | 25/28 [00:07<00:00, 3.47it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.47it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.47it/s]\n100%|██████████| 28/28 [00:08<00:00, 3.47it/s]\n100%|██████████| 28/28 [00:08<00:00, 3.49it/s]", "metrics": { "predict_time": 16.577002482, "total_time": 22.48497 }, "output": [ "https://replicate.delivery/yhqm/fuFbIUf2WZprcUsPh8fBbRCxXBx9fWRvSn4Bx1YNenFeLod2E/out-0.webp" ], "started_at": "2024-09-05T13:46:06.878968Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/ed1q74thhdrm60chr9qt0ra05w", "cancel": "https://api.replicate.com/v1/predictions/ed1q74thhdrm60chr9qt0ra05w/cancel" }, "version": "23cd3151875f9caf78b022d9409425d04e3a5b0fa093d07590b37d3f98fef682" }Generated inUsing seed: 7564 Prompt: a MNCRFTMOV film render of a goofy blocky tiger txt2img mode Using dev model Loaded LoRAs in 7.99s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.47it/s] 7%|▋ | 2/28 [00:00<00:06, 3.93it/s] 11%|█ | 3/28 [00:00<00:06, 3.71it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.61it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.56it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.53it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.51it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.50it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.49it/s] 36%|███▌ | 10/28 [00:02<00:05, 3.48it/s] 39%|███▉ | 11/28 [00:03<00:04, 3.48it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.48it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.47it/s] 50%|█████ | 14/28 [00:03<00:04, 3.47it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.47it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.47it/s] 61%|██████ | 17/28 [00:04<00:03, 3.47it/s] 64%|██████▍ | 18/28 [00:05<00:02, 3.47it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.47it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.47it/s] 75%|███████▌ | 21/28 [00:05<00:02, 3.47it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.47it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.47it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.47it/s] 89%|████████▉ | 25/28 [00:07<00:00, 3.47it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.47it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.47it/s] 100%|██████████| 28/28 [00:08<00:00, 3.47it/s] 100%|██████████| 28/28 [00:08<00:00, 3.49it/s]Prediction
fofr/flux-minecraft-movie:23cd3151875f9caf78b022d9409425d04e3a5b0fa093d07590b37d3f98fef682ID0c90gvhjvnrm20chr9raccz0scStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a MNCRFTMOV film render of a blocky cyberpunk
- 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 MNCRFTMOV film render of a blocky cyberpunk", "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 replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/flux-minecraft-movie using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-minecraft-movie:23cd3151875f9caf78b022d9409425d04e3a5b0fa093d07590b37d3f98fef682", { input: { model: "dev", prompt: "a MNCRFTMOV film render of a blocky cyberpunk", 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 } } ); // 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 fofr/flux-minecraft-movie using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-minecraft-movie:23cd3151875f9caf78b022d9409425d04e3a5b0fa093d07590b37d3f98fef682", input={ "model": "dev", "prompt": "a MNCRFTMOV film render of a blocky cyberpunk", "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.
Run fofr/flux-minecraft-movie 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": "fofr/flux-minecraft-movie:23cd3151875f9caf78b022d9409425d04e3a5b0fa093d07590b37d3f98fef682", "input": { "model": "dev", "prompt": "a MNCRFTMOV film render of a blocky cyberpunk", "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": "2024-09-05T13:47:16.711669Z", "created_at": "2024-09-05T13:46:58.653000Z", "data_removed": false, "error": null, "id": "0c90gvhjvnrm20chr9raccz0sc", "input": { "model": "dev", "prompt": "a MNCRFTMOV film render of a blocky cyberpunk", "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: 53192\nPrompt: a MNCRFTMOV film render of a blocky cyberpunk\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 9.42s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.45it/s]\n 7%|▋ | 2/28 [00:00<00:06, 3.89it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.68it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.58it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.53it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.51it/s]\n 25%|██▌ | 7/28 [00:01<00:06, 3.49it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.47it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.46it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.46it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.45it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.45it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.45it/s]\n 50%|█████ | 14/28 [00:04<00:04, 3.44it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.45it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.45it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.44it/s]\n 64%|██████▍ | 18/28 [00:05<00:02, 3.44it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.44it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.44it/s]\n 75%|███████▌ | 21/28 [00:06<00:02, 3.44it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.44it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.44it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.44it/s]\n 89%|████████▉ | 25/28 [00:07<00:00, 3.44it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.44it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.44it/s]\n100%|██████████| 28/28 [00:08<00:00, 3.44it/s]\n100%|██████████| 28/28 [00:08<00:00, 3.47it/s]", "metrics": { "predict_time": 18.048668263, "total_time": 18.058669 }, "output": [ "https://replicate.delivery/yhqm/5gLXpwkKSpY8DF0ilq5AlbHo3R8wMej96PQ73r1fEoZkh2ZTA/out-0.webp" ], "started_at": "2024-09-05T13:46:58.663000Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/0c90gvhjvnrm20chr9raccz0sc", "cancel": "https://api.replicate.com/v1/predictions/0c90gvhjvnrm20chr9raccz0sc/cancel" }, "version": "23cd3151875f9caf78b022d9409425d04e3a5b0fa093d07590b37d3f98fef682" }Generated inUsing seed: 53192 Prompt: a MNCRFTMOV film render of a blocky cyberpunk txt2img mode Using dev model Loaded LoRAs in 9.42s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.45it/s] 7%|▋ | 2/28 [00:00<00:06, 3.89it/s] 11%|█ | 3/28 [00:00<00:06, 3.68it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.58it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.53it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.51it/s] 25%|██▌ | 7/28 [00:01<00:06, 3.49it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.47it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.46it/s] 36%|███▌ | 10/28 [00:02<00:05, 3.46it/s] 39%|███▉ | 11/28 [00:03<00:04, 3.45it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.45it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.45it/s] 50%|█████ | 14/28 [00:04<00:04, 3.44it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.45it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.45it/s] 61%|██████ | 17/28 [00:04<00:03, 3.44it/s] 64%|██████▍ | 18/28 [00:05<00:02, 3.44it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.44it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.44it/s] 75%|███████▌ | 21/28 [00:06<00:02, 3.44it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.44it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.44it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.44it/s] 89%|████████▉ | 25/28 [00:07<00:00, 3.44it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.44it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.44it/s] 100%|██████████| 28/28 [00:08<00:00, 3.44it/s] 100%|██████████| 28/28 [00:08<00:00, 3.47it/s]
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