fofr
/
flux-meta-orion
Flux lora, use the word "META_ORION_GLASSES" to trigger generation
- Public
- 186 runs
-
H100
- Weights
Prediction
fofr/flux-meta-orion:da4211bdIDe6j327jjk9rm20cj5q3bhfzemrStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a photo of someone wearing META_ORION_GLASSES
- 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 photo of someone wearing META_ORION_GLASSES", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/flux-meta-orion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-meta-orion:da4211bdbe4ed26a23ff53d16731adc5b4f828159d615bd51dc5ea90ee1c1b36", { input: { model: "dev", prompt: "a photo of someone wearing META_ORION_GLASSES", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun fofr/flux-meta-orion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-meta-orion:da4211bdbe4ed26a23ff53d16731adc5b4f828159d615bd51dc5ea90ee1c1b36", input={ "model": "dev", "prompt": "a photo of someone wearing META_ORION_GLASSES", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run fofr/flux-meta-orion 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": "da4211bdbe4ed26a23ff53d16731adc5b4f828159d615bd51dc5ea90ee1c1b36", "input": { "model": "dev", "prompt": "a photo of someone wearing META_ORION_GLASSES", "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": "2024-09-26T10:00:43.046250Z", "created_at": "2024-09-26T10:00:24.986000Z", "data_removed": false, "error": null, "id": "e6j327jjk9rm20cj5q3bhfzemr", "input": { "model": "dev", "prompt": "a photo of someone wearing META_ORION_GLASSES", "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: 39445\nPrompt: a photo of someone wearing META_ORION_GLASSES\n[!] txt2img mode\nUsing dev model\nfree=7915958915072\nDownloading weights\n2024-09-26T10:00:25Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp535mm7r7/weights url=https://replicate.delivery/yhqm/V0jUMJtODJ4ZL9RJBADOx3p8WnOIBhoPn0UszHGHdJle2WwJA/trained_model.tar\n2024-09-26T10:00:27Z | INFO | [ Complete ] dest=/tmp/tmp535mm7r7/weights size=\"172 MB\" total_elapsed=2.101s url=https://replicate.delivery/yhqm/V0jUMJtODJ4ZL9RJBADOx3p8WnOIBhoPn0UszHGHdJle2WwJA/trained_model.tar\nDownloaded weights in 2.14s\nLoaded LoRAs in 9.55s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.52it/s]\n 7%|▋ | 2/28 [00:00<00:06, 3.98it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.75it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.65it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.60it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.57it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.55it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.54it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.53it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.52it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.52it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.52it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.52it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.51it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.51it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.51it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.51it/s]\n 64%|██████▍ | 18/28 [00:05<00:02, 3.51it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.51it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.51it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.51it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.50it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.51it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.51it/s]\n 89%|████████▉ | 25/28 [00:07<00:00, 3.51it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.51it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.50it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.50it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.53it/s]", "metrics": { "predict_time": 18.025203969, "total_time": 18.06025 }, "output": [ "https://replicate.delivery/yhqm/JT5fIycVGW2YR6SB8f2rNuP1dJQPdCayItP3uv0VXihKLugTA/out-0.webp" ], "started_at": "2024-09-26T10:00:25.021046Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/e6j327jjk9rm20cj5q3bhfzemr", "cancel": "https://api.replicate.com/v1/predictions/e6j327jjk9rm20cj5q3bhfzemr/cancel" }, "version": "da4211bdbe4ed26a23ff53d16731adc5b4f828159d615bd51dc5ea90ee1c1b36" }Generated inUsing seed: 39445 Prompt: a photo of someone wearing META_ORION_GLASSES [!] txt2img mode Using dev model free=7915958915072 Downloading weights 2024-09-26T10:00:25Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp535mm7r7/weights url=https://replicate.delivery/yhqm/V0jUMJtODJ4ZL9RJBADOx3p8WnOIBhoPn0UszHGHdJle2WwJA/trained_model.tar 2024-09-26T10:00:27Z | INFO | [ Complete ] dest=/tmp/tmp535mm7r7/weights size="172 MB" total_elapsed=2.101s url=https://replicate.delivery/yhqm/V0jUMJtODJ4ZL9RJBADOx3p8WnOIBhoPn0UszHGHdJle2WwJA/trained_model.tar Downloaded weights in 2.14s Loaded LoRAs in 9.55s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.52it/s] 7%|▋ | 2/28 [00:00<00:06, 3.98it/s] 11%|█ | 3/28 [00:00<00:06, 3.75it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.65it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.60it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.57it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.55it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.54it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.53it/s] 36%|███▌ | 10/28 [00:02<00:05, 3.52it/s] 39%|███▉ | 11/28 [00:03<00:04, 3.52it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.52it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.52it/s] 50%|█████ | 14/28 [00:03<00:03, 3.51it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.51it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.51it/s] 61%|██████ | 17/28 [00:04<00:03, 3.51it/s] 64%|██████▍ | 18/28 [00:05<00:02, 3.51it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.51it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.51it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.51it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.50it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.51it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.51it/s] 89%|████████▉ | 25/28 [00:07<00:00, 3.51it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.51it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.50it/s] 100%|██████████| 28/28 [00:07<00:00, 3.50it/s] 100%|██████████| 28/28 [00:07<00:00, 3.53it/s]Prediction
fofr/flux-meta-orion:da4211bdID7mqxdsxh51rm40cj5q48kckpm0StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a photo of a cat wearing META_ORION_GLASSES
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a photo of a cat wearing META_ORION_GLASSES", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/flux-meta-orion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-meta-orion:da4211bdbe4ed26a23ff53d16731adc5b4f828159d615bd51dc5ea90ee1c1b36", { input: { model: "dev", prompt: "a photo of a cat wearing META_ORION_GLASSES", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun fofr/flux-meta-orion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-meta-orion:da4211bdbe4ed26a23ff53d16731adc5b4f828159d615bd51dc5ea90ee1c1b36", input={ "model": "dev", "prompt": "a photo of a cat wearing META_ORION_GLASSES", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run fofr/flux-meta-orion 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": "da4211bdbe4ed26a23ff53d16731adc5b4f828159d615bd51dc5ea90ee1c1b36", "input": { "model": "dev", "prompt": "a photo of a cat wearing META_ORION_GLASSES", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "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": "2024-09-26T10:03:31.353292Z", "created_at": "2024-09-26T10:03:00.264000Z", "data_removed": false, "error": null, "id": "7mqxdsxh51rm40cj5q48kckpm0", "input": { "model": "dev", "prompt": "a photo of a cat wearing META_ORION_GLASSES", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 3503\nPrompt: a photo of a cat wearing META_ORION_GLASSES\n[!] txt2img mode\nUsing dev model\nfree=7066774999040\nDownloading weights\n2024-09-26T10:03:13Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp5ytzfmav/weights url=https://replicate.delivery/yhqm/V0jUMJtODJ4ZL9RJBADOx3p8WnOIBhoPn0UszHGHdJle2WwJA/trained_model.tar\n2024-09-26T10:03:15Z | INFO | [ Complete ] dest=/tmp/tmp5ytzfmav/weights size=\"172 MB\" total_elapsed=1.321s url=https://replicate.delivery/yhqm/V0jUMJtODJ4ZL9RJBADOx3p8WnOIBhoPn0UszHGHdJle2WwJA/trained_model.tar\nDownloaded weights in 1.35s\nLoaded LoRAs in 9.18s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.50it/s]\n 7%|▋ | 2/28 [00:00<00:06, 3.97it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.74it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.64it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.58it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.55it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.54it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.52it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.52it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.51it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.51it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.50it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.50it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.50it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.50it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.50it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.50it/s]\n 64%|██████▍ | 18/28 [00:05<00:02, 3.50it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.50it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.50it/s]\n 75%|███████▌ | 21/28 [00:05<00:02, 3.50it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.50it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.50it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.50it/s]\n 89%|████████▉ | 25/28 [00:07<00:00, 3.50it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.50it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.50it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.50it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.52it/s]", "metrics": { "predict_time": 17.684232577, "total_time": 31.089292 }, "output": [ "https://replicate.delivery/yhqm/BnRsOXeL7DzIKSyL7Kw45sEUilgr8myHsseKRXLtE7yzNugTA/out-0.webp" ], "started_at": "2024-09-26T10:03:13.669060Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/7mqxdsxh51rm40cj5q48kckpm0", "cancel": "https://api.replicate.com/v1/predictions/7mqxdsxh51rm40cj5q48kckpm0/cancel" }, "version": "da4211bdbe4ed26a23ff53d16731adc5b4f828159d615bd51dc5ea90ee1c1b36" }Generated inUsing seed: 3503 Prompt: a photo of a cat wearing META_ORION_GLASSES [!] txt2img mode Using dev model free=7066774999040 Downloading weights 2024-09-26T10:03:13Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp5ytzfmav/weights url=https://replicate.delivery/yhqm/V0jUMJtODJ4ZL9RJBADOx3p8WnOIBhoPn0UszHGHdJle2WwJA/trained_model.tar 2024-09-26T10:03:15Z | INFO | [ Complete ] dest=/tmp/tmp5ytzfmav/weights size="172 MB" total_elapsed=1.321s url=https://replicate.delivery/yhqm/V0jUMJtODJ4ZL9RJBADOx3p8WnOIBhoPn0UszHGHdJle2WwJA/trained_model.tar Downloaded weights in 1.35s Loaded LoRAs in 9.18s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.50it/s] 7%|▋ | 2/28 [00:00<00:06, 3.97it/s] 11%|█ | 3/28 [00:00<00:06, 3.74it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.64it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.58it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.55it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.54it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.52it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.52it/s] 36%|███▌ | 10/28 [00:02<00:05, 3.51it/s] 39%|███▉ | 11/28 [00:03<00:04, 3.51it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.50it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.50it/s] 50%|█████ | 14/28 [00:03<00:03, 3.50it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.50it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.50it/s] 61%|██████ | 17/28 [00:04<00:03, 3.50it/s] 64%|██████▍ | 18/28 [00:05<00:02, 3.50it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.50it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.50it/s] 75%|███████▌ | 21/28 [00:05<00:02, 3.50it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.50it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.50it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.50it/s] 89%|████████▉ | 25/28 [00:07<00:00, 3.50it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.50it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.50it/s] 100%|██████████| 28/28 [00:07<00:00, 3.50it/s] 100%|██████████| 28/28 [00:07<00:00, 3.52it/s]Prediction
fofr/flux-meta-orion:da4211bdID4mqjwmsrc9rm00cj5rctv71xmwStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a photo of MNALSA wearing META_ORION_GLASSES presenting as a tech ceo woman presenting at a conference on stage
- extra_lora
- fofr/flux-mona-lisa
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 3:4
- output_format
- webp
- guidance_scale
- 2.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a photo of MNALSA wearing META_ORION_GLASSES presenting as a tech ceo woman presenting at a conference on stage", "extra_lora": "fofr/flux-mona-lisa", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "3:4", "output_format": "webp", "guidance_scale": 2.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/flux-meta-orion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-meta-orion:da4211bdbe4ed26a23ff53d16731adc5b4f828159d615bd51dc5ea90ee1c1b36", { input: { model: "dev", prompt: "a photo of MNALSA wearing META_ORION_GLASSES presenting as a tech ceo woman presenting at a conference on stage", extra_lora: "fofr/flux-mona-lisa", lora_scale: 1, num_outputs: 4, aspect_ratio: "3:4", output_format: "webp", guidance_scale: 2.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun fofr/flux-meta-orion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-meta-orion:da4211bdbe4ed26a23ff53d16731adc5b4f828159d615bd51dc5ea90ee1c1b36", input={ "model": "dev", "prompt": "a photo of MNALSA wearing META_ORION_GLASSES presenting as a tech ceo woman presenting at a conference on stage", "extra_lora": "fofr/flux-mona-lisa", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "3:4", "output_format": "webp", "guidance_scale": 2.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run fofr/flux-meta-orion 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": "da4211bdbe4ed26a23ff53d16731adc5b4f828159d615bd51dc5ea90ee1c1b36", "input": { "model": "dev", "prompt": "a photo of MNALSA wearing META_ORION_GLASSES presenting as a tech ceo woman presenting at a conference on stage", "extra_lora": "fofr/flux-mona-lisa", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "3:4", "output_format": "webp", "guidance_scale": 2.5, "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": "2024-09-26T11:32:04.790212Z", "created_at": "2024-09-26T11:30:57.762000Z", "data_removed": false, "error": null, "id": "4mqjwmsrc9rm00cj5rctv71xmw", "input": { "model": "dev", "prompt": "a photo of MNALSA wearing META_ORION_GLASSES presenting as a tech ceo woman presenting at a conference on stage", "extra_lora": "fofr/flux-mona-lisa", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "3:4", "output_format": "webp", "guidance_scale": 2.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 8750\nPrompt: a photo of MNALSA wearing META_ORION_GLASSES presenting as a tech ceo woman presenting at a conference on stage\n[!] txt2img mode\nUsing dev model\nLoading extra LoRA weights from: fofr/flux-mona-lisa\nfree=7725553537024\nDownloading weights\n2024-09-26T11:30:57Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpfu4fb2km/weights url=https://replicate.delivery/yhqm/V0jUMJtODJ4ZL9RJBADOx3p8WnOIBhoPn0UszHGHdJle2WwJA/trained_model.tar\n2024-09-26T11:30:59Z | INFO | [ Complete ] dest=/tmp/tmpfu4fb2km/weights size=\"172 MB\" total_elapsed=1.176s url=https://replicate.delivery/yhqm/V0jUMJtODJ4ZL9RJBADOx3p8WnOIBhoPn0UszHGHdJle2WwJA/trained_model.tar\nDownloaded weights in 1.27s\nfree=7725381447680\nDownloading weights\n2024-09-26T11:31:17Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp1qbw4c4b/weights url=https://replicate.com/fofr/flux-mona-lisa/_weights\n2024-09-26T11:31:18Z | INFO | [ Redirect ] redirect_url=https://replicate.delivery/yhqm/oeMZkUBoPczvPKVwht0tS5O2D8yeL2hGJV4XMj2qqxRAHrWTA/trained_model.tar url=https://replicate.com/fofr/flux-mona-lisa/_weights\n2024-09-26T11:31:19Z | INFO | [ Complete ] dest=/tmp/tmp1qbw4c4b/weights size=\"172 MB\" total_elapsed=1.447s url=https://replicate.com/fofr/flux-mona-lisa/_weights\nDownloaded weights in 1.48s\nLoaded LoRAs in 32.59s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:31, 1.17s/it]\n 7%|▋ | 2/28 [00:02<00:27, 1.07s/it]\n 11%|█ | 3/28 [00:03<00:27, 1.12s/it]\n 14%|█▍ | 4/28 [00:04<00:27, 1.14s/it]\n 18%|█▊ | 5/28 [00:05<00:26, 1.15s/it]\n 21%|██▏ | 6/28 [00:06<00:25, 1.16s/it]\n 25%|██▌ | 7/28 [00:08<00:24, 1.16s/it]\n 29%|██▊ | 8/28 [00:09<00:23, 1.17s/it]\n 32%|███▏ | 9/28 [00:10<00:22, 1.17s/it]\n 36%|███▌ | 10/28 [00:11<00:21, 1.17s/it]\n 39%|███▉ | 11/28 [00:12<00:19, 1.17s/it]\n 43%|████▎ | 12/28 [00:13<00:18, 1.17s/it]\n 46%|████▋ | 13/28 [00:15<00:17, 1.17s/it]\n 50%|█████ | 14/28 [00:16<00:16, 1.17s/it]\n 54%|█████▎ | 15/28 [00:17<00:15, 1.17s/it]\n 57%|█████▋ | 16/28 [00:18<00:14, 1.17s/it]\n 61%|██████ | 17/28 [00:19<00:12, 1.17s/it]\n 64%|██████▍ | 18/28 [00:20<00:11, 1.18s/it]\n 68%|██████▊ | 19/28 [00:22<00:10, 1.18s/it]\n 71%|███████▏ | 20/28 [00:23<00:09, 1.18s/it]\n 75%|███████▌ | 21/28 [00:24<00:08, 1.18s/it]\n 79%|███████▊ | 22/28 [00:25<00:07, 1.18s/it]\n 82%|████████▏ | 23/28 [00:26<00:05, 1.18s/it]\n 86%|████████▌ | 24/28 [00:28<00:04, 1.18s/it]\n 89%|████████▉ | 25/28 [00:29<00:03, 1.18s/it]\n 93%|█████████▎| 26/28 [00:30<00:02, 1.18s/it]\n 96%|█████████▋| 27/28 [00:31<00:01, 1.18s/it]\n100%|██████████| 28/28 [00:32<00:00, 1.18s/it]\n100%|██████████| 28/28 [00:32<00:00, 1.17s/it]", "metrics": { "predict_time": 66.992639192, "total_time": 67.028212 }, "output": [ "https://replicate.delivery/yhqm/AfvDsuKZx2zvWivk8MivovH1e1epFNf7BDiXpGw4wPsRDeFcC/out-0.webp", "https://replicate.delivery/yhqm/OIlHJxw72IZZA9OBiPzZcGelXx5ugFuSgLYLsSymD3XawXwJA/out-1.webp", "https://replicate.delivery/yhqm/wbEfXJT3gCX1YCRGLjaBrCguefePW8ceIVYimrmwXpunG8FcC/out-2.webp", "https://replicate.delivery/yhqm/Zr3dMZNzDPLwIBwbVe4tJHDQ7IhvlGIIRhe5RM4RoqN0gvgTA/out-3.webp" ], "started_at": "2024-09-26T11:30:57.797573Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/4mqjwmsrc9rm00cj5rctv71xmw", "cancel": "https://api.replicate.com/v1/predictions/4mqjwmsrc9rm00cj5rctv71xmw/cancel" }, "version": "da4211bdbe4ed26a23ff53d16731adc5b4f828159d615bd51dc5ea90ee1c1b36" }Generated inUsing seed: 8750 Prompt: a photo of MNALSA wearing META_ORION_GLASSES presenting as a tech ceo woman presenting at a conference on stage [!] txt2img mode Using dev model Loading extra LoRA weights from: fofr/flux-mona-lisa free=7725553537024 Downloading weights 2024-09-26T11:30:57Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpfu4fb2km/weights url=https://replicate.delivery/yhqm/V0jUMJtODJ4ZL9RJBADOx3p8WnOIBhoPn0UszHGHdJle2WwJA/trained_model.tar 2024-09-26T11:30:59Z | INFO | [ Complete ] dest=/tmp/tmpfu4fb2km/weights size="172 MB" total_elapsed=1.176s url=https://replicate.delivery/yhqm/V0jUMJtODJ4ZL9RJBADOx3p8WnOIBhoPn0UszHGHdJle2WwJA/trained_model.tar Downloaded weights in 1.27s free=7725381447680 Downloading weights 2024-09-26T11:31:17Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp1qbw4c4b/weights url=https://replicate.com/fofr/flux-mona-lisa/_weights 2024-09-26T11:31:18Z | INFO | [ Redirect ] redirect_url=https://replicate.delivery/yhqm/oeMZkUBoPczvPKVwht0tS5O2D8yeL2hGJV4XMj2qqxRAHrWTA/trained_model.tar url=https://replicate.com/fofr/flux-mona-lisa/_weights 2024-09-26T11:31:19Z | INFO | [ Complete ] dest=/tmp/tmp1qbw4c4b/weights size="172 MB" total_elapsed=1.447s url=https://replicate.com/fofr/flux-mona-lisa/_weights Downloaded weights in 1.48s Loaded LoRAs in 32.59s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:31, 1.17s/it] 7%|▋ | 2/28 [00:02<00:27, 1.07s/it] 11%|█ | 3/28 [00:03<00:27, 1.12s/it] 14%|█▍ | 4/28 [00:04<00:27, 1.14s/it] 18%|█▊ | 5/28 [00:05<00:26, 1.15s/it] 21%|██▏ | 6/28 [00:06<00:25, 1.16s/it] 25%|██▌ | 7/28 [00:08<00:24, 1.16s/it] 29%|██▊ | 8/28 [00:09<00:23, 1.17s/it] 32%|███▏ | 9/28 [00:10<00:22, 1.17s/it] 36%|███▌ | 10/28 [00:11<00:21, 1.17s/it] 39%|███▉ | 11/28 [00:12<00:19, 1.17s/it] 43%|████▎ | 12/28 [00:13<00:18, 1.17s/it] 46%|████▋ | 13/28 [00:15<00:17, 1.17s/it] 50%|█████ | 14/28 [00:16<00:16, 1.17s/it] 54%|█████▎ | 15/28 [00:17<00:15, 1.17s/it] 57%|█████▋ | 16/28 [00:18<00:14, 1.17s/it] 61%|██████ | 17/28 [00:19<00:12, 1.17s/it] 64%|██████▍ | 18/28 [00:20<00:11, 1.18s/it] 68%|██████▊ | 19/28 [00:22<00:10, 1.18s/it] 71%|███████▏ | 20/28 [00:23<00:09, 1.18s/it] 75%|███████▌ | 21/28 [00:24<00:08, 1.18s/it] 79%|███████▊ | 22/28 [00:25<00:07, 1.18s/it] 82%|████████▏ | 23/28 [00:26<00:05, 1.18s/it] 86%|████████▌ | 24/28 [00:28<00:04, 1.18s/it] 89%|████████▉ | 25/28 [00:29<00:03, 1.18s/it] 93%|█████████▎| 26/28 [00:30<00:02, 1.18s/it] 96%|█████████▋| 27/28 [00:31<00:01, 1.18s/it] 100%|██████████| 28/28 [00:32<00:00, 1.18s/it] 100%|██████████| 28/28 [00:32<00:00, 1.17s/it]
Want to make some of these yourself?
Run this model