fofr
/
flux-tesla-cybercab
Flux lora, use "CYBERCAB" to trigger generations
- Public
- 278 runs
-
H100
- Weights
Prediction
fofr/flux-tesla-cybercab:5e6178aaInput
- model
- dev
- prompt
- A photo of a CYBERCAB
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 3:2
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
- disable_safety_checker
{ "model": "dev", "prompt": "A photo of a CYBERCAB", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28, "disable_safety_checker": false }npm install replicateSet theREPLICATE_API_TOKENenvironment 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 fofr/flux-tesla-cybercab using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-tesla-cybercab:5e6178aa59d0653f3a649ab6cdd0603e524d5a7e57401c29f6c9ebe13e84c2f9", { input: { model: "dev", prompt: "A photo of a CYBERCAB", lora_scale: 1, num_outputs: 1, aspect_ratio: "3:2", 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.
pip install replicateSet theREPLICATE_API_TOKENenvironment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the clientimport replicateRun fofr/flux-tesla-cybercab using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-tesla-cybercab:5e6178aa59d0653f3a649ab6cdd0603e524d5a7e57401c29f6c9ebe13e84c2f9", input={ "model": "dev", "prompt": "A photo of a CYBERCAB", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "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 variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run fofr/flux-tesla-cybercab 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": "5e6178aa59d0653f3a649ab6cdd0603e524d5a7e57401c29f6c9ebe13e84c2f9", "input": { "model": "dev", "prompt": "A photo of a CYBERCAB", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "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": "2024-10-11T10:03:16.929733Z", "created_at": "2024-10-11T10:03:04.969000Z", "data_removed": false, "error": null, "id": "jqhjme17h5rm20cjfc4842d8r0", "input": { "model": "dev", "prompt": "A photo of a CYBERCAB", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28, "disable_safety_checker": false }, "logs": "Using seed: 37090\nPrompt: A photo of a CYBERCAB\n[!] txt2img mode\nUsing dev model\nfree=6855159570432\nDownloading weights\n2024-10-11T10:03:05Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpbxycokpu/weights url=https://replicate.delivery/yhqm/zer7jDTdcWTlIKo2lXz1qLGHj2piBy1BdaMerWksKLoEkqlTA/trained_model.tar\n2024-10-11T10:03:06Z | INFO | [ Complete ] dest=/tmp/tmpbxycokpu/weights size=\"172 MB\" total_elapsed=1.394s url=https://replicate.delivery/yhqm/zer7jDTdcWTlIKo2lXz1qLGHj2piBy1BdaMerWksKLoEkqlTA/trained_model.tar\nDownloaded weights in 1.42s\nLoaded LoRAs in 2.17s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:09, 2.94it/s]\n 7%|▋ | 2/28 [00:00<00:07, 3.28it/s]\n 11%|█ | 3/28 [00:00<00:08, 3.12it/s]\n 14%|█▍ | 4/28 [00:01<00:07, 3.04it/s]\n 18%|█▊ | 5/28 [00:01<00:07, 3.01it/s]\n 21%|██▏ | 6/28 [00:01<00:07, 2.98it/s]\n 25%|██▌ | 7/28 [00:02<00:07, 2.97it/s]\n 29%|██▊ | 8/28 [00:02<00:06, 2.96it/s]\n 32%|███▏ | 9/28 [00:03<00:06, 2.96it/s]\n 36%|███▌ | 10/28 [00:03<00:06, 2.95it/s]\n 39%|███▉ | 11/28 [00:03<00:05, 2.95it/s]\n 43%|████▎ | 12/28 [00:04<00:05, 2.95it/s]\n 46%|████▋ | 13/28 [00:04<00:05, 2.95it/s]\n 50%|█████ | 14/28 [00:04<00:04, 2.95it/s]\n 54%|█████▎ | 15/28 [00:05<00:04, 2.95it/s]\n 57%|█████▋ | 16/28 [00:05<00:04, 2.95it/s]\n 61%|██████ | 17/28 [00:05<00:03, 2.95it/s]\n 64%|██████▍ | 18/28 [00:06<00:03, 2.95it/s]\n 68%|██████▊ | 19/28 [00:06<00:03, 2.95it/s]\n 71%|███████▏ | 20/28 [00:06<00:02, 2.95it/s]\n 75%|███████▌ | 21/28 [00:07<00:02, 2.95it/s]\n 79%|███████▊ | 22/28 [00:07<00:02, 2.95it/s]\n 82%|████████▏ | 23/28 [00:07<00:01, 2.95it/s]\n 86%|████████▌ | 24/28 [00:08<00:01, 2.95it/s]\n 89%|████████▉ | 25/28 [00:08<00:01, 2.95it/s]\n 93%|█████████▎| 26/28 [00:08<00:00, 2.95it/s]\n 96%|█████████▋| 27/28 [00:09<00:00, 2.95it/s]\n100%|██████████| 28/28 [00:09<00:00, 2.95it/s]\n100%|██████████| 28/28 [00:09<00:00, 2.96it/s]", "metrics": { "predict_time": 11.954976705, "total_time": 11.960733 }, "output": [ "https://replicate.delivery/yhqm/RoDifKKcSm3ONSyKeqUA2GziNAavgeOI3r4WwuIBxfuTeUtcC/out-0.webp" ], "started_at": "2024-10-11T10:03:04.974756Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/jqhjme17h5rm20cjfc4842d8r0", "cancel": "https://api.replicate.com/v1/predictions/jqhjme17h5rm20cjfc4842d8r0/cancel" }, "version": "5e6178aa59d0653f3a649ab6cdd0603e524d5a7e57401c29f6c9ebe13e84c2f9" }Generated inUsing seed: 37090 Prompt: A photo of a CYBERCAB [!] txt2img mode Using dev model free=6855159570432 Downloading weights 2024-10-11T10:03:05Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpbxycokpu/weights url=https://replicate.delivery/yhqm/zer7jDTdcWTlIKo2lXz1qLGHj2piBy1BdaMerWksKLoEkqlTA/trained_model.tar 2024-10-11T10:03:06Z | INFO | [ Complete ] dest=/tmp/tmpbxycokpu/weights size="172 MB" total_elapsed=1.394s url=https://replicate.delivery/yhqm/zer7jDTdcWTlIKo2lXz1qLGHj2piBy1BdaMerWksKLoEkqlTA/trained_model.tar Downloaded weights in 1.42s Loaded LoRAs in 2.17s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:09, 2.94it/s] 7%|▋ | 2/28 [00:00<00:07, 3.28it/s] 11%|█ | 3/28 [00:00<00:08, 3.12it/s] 14%|█▍ | 4/28 [00:01<00:07, 3.04it/s] 18%|█▊ | 5/28 [00:01<00:07, 3.01it/s] 21%|██▏ | 6/28 [00:01<00:07, 2.98it/s] 25%|██▌ | 7/28 [00:02<00:07, 2.97it/s] 29%|██▊ | 8/28 [00:02<00:06, 2.96it/s] 32%|███▏ | 9/28 [00:03<00:06, 2.96it/s] 36%|███▌ | 10/28 [00:03<00:06, 2.95it/s] 39%|███▉ | 11/28 [00:03<00:05, 2.95it/s] 43%|████▎ | 12/28 [00:04<00:05, 2.95it/s] 46%|████▋ | 13/28 [00:04<00:05, 2.95it/s] 50%|█████ | 14/28 [00:04<00:04, 2.95it/s] 54%|█████▎ | 15/28 [00:05<00:04, 2.95it/s] 57%|█████▋ | 16/28 [00:05<00:04, 2.95it/s] 61%|██████ | 17/28 [00:05<00:03, 2.95it/s] 64%|██████▍ | 18/28 [00:06<00:03, 2.95it/s] 68%|██████▊ | 19/28 [00:06<00:03, 2.95it/s] 71%|███████▏ | 20/28 [00:06<00:02, 2.95it/s] 75%|███████▌ | 21/28 [00:07<00:02, 2.95it/s] 79%|███████▊ | 22/28 [00:07<00:02, 2.95it/s] 82%|████████▏ | 23/28 [00:07<00:01, 2.95it/s] 86%|████████▌ | 24/28 [00:08<00:01, 2.95it/s] 89%|████████▉ | 25/28 [00:08<00:01, 2.95it/s] 93%|█████████▎| 26/28 [00:08<00:00, 2.95it/s] 96%|█████████▋| 27/28 [00:09<00:00, 2.95it/s] 100%|██████████| 28/28 [00:09<00:00, 2.95it/s] 100%|██████████| 28/28 [00:09<00:00, 2.96it/s]Prediction
fofr/flux-tesla-cybercab:5e6178aaID8xyp99sz1nrm60cjfc4vzhga9mStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- A photo of a CYBERCAB with one door open, in San Francisco
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 3:2
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
- disable_safety_checker
{ "model": "dev", "prompt": "A photo of a CYBERCAB with one door open, in San Francisco", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28, "disable_safety_checker": false }npm install replicateSet theREPLICATE_API_TOKENenvironment 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 fofr/flux-tesla-cybercab using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-tesla-cybercab:5e6178aa59d0653f3a649ab6cdd0603e524d5a7e57401c29f6c9ebe13e84c2f9", { input: { model: "dev", prompt: "A photo of a CYBERCAB with one door open, in San Francisco", lora_scale: 1, num_outputs: 1, aspect_ratio: "3:2", 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.
pip install replicateSet theREPLICATE_API_TOKENenvironment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the clientimport replicateRun fofr/flux-tesla-cybercab using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-tesla-cybercab:5e6178aa59d0653f3a649ab6cdd0603e524d5a7e57401c29f6c9ebe13e84c2f9", input={ "model": "dev", "prompt": "A photo of a CYBERCAB with one door open, in San Francisco", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "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 variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run fofr/flux-tesla-cybercab 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": "5e6178aa59d0653f3a649ab6cdd0603e524d5a7e57401c29f6c9ebe13e84c2f9", "input": { "model": "dev", "prompt": "A photo of a CYBERCAB with one door open, in San Francisco", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "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": "2024-10-11T10:04:28.077425Z", "created_at": "2024-10-11T10:04:16.525000Z", "data_removed": false, "error": null, "id": "8xyp99sz1nrm60cjfc4vzhga9m", "input": { "model": "dev", "prompt": "A photo of a CYBERCAB with one door open, in San Francisco", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28, "disable_safety_checker": false }, "logs": "Using seed: 51996\nPrompt: A photo of a CYBERCAB with one door open, in San Francisco\n[!] txt2img mode\nUsing dev model\nfree=7544279883776\nDownloading weights\n2024-10-11T10:04:16Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpkvm_rqao/weights url=https://replicate.delivery/yhqm/zer7jDTdcWTlIKo2lXz1qLGHj2piBy1BdaMerWksKLoEkqlTA/trained_model.tar\n2024-10-11T10:04:17Z | INFO | [ Complete ] dest=/tmp/tmpkvm_rqao/weights size=\"172 MB\" total_elapsed=1.025s url=https://replicate.delivery/yhqm/zer7jDTdcWTlIKo2lXz1qLGHj2piBy1BdaMerWksKLoEkqlTA/trained_model.tar\nDownloaded weights in 1.05s\nLoaded LoRAs in 1.78s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:09, 2.95it/s]\n 7%|▋ | 2/28 [00:00<00:07, 3.29it/s]\n 11%|█ | 3/28 [00:00<00:07, 3.13it/s]\n 14%|█▍ | 4/28 [00:01<00:07, 3.06it/s]\n 18%|█▊ | 5/28 [00:01<00:07, 3.02it/s]\n 21%|██▏ | 6/28 [00:01<00:07, 3.00it/s]\n 25%|██▌ | 7/28 [00:02<00:07, 2.98it/s]\n 29%|██▊ | 8/28 [00:02<00:06, 2.97it/s]\n 32%|███▏ | 9/28 [00:02<00:06, 2.97it/s]\n 36%|███▌ | 10/28 [00:03<00:06, 2.96it/s]\n 39%|███▉ | 11/28 [00:03<00:05, 2.96it/s]\n 43%|████▎ | 12/28 [00:04<00:05, 2.96it/s]\n 46%|████▋ | 13/28 [00:04<00:05, 2.96it/s]\n 50%|█████ | 14/28 [00:04<00:04, 2.96it/s]\n 54%|█████▎ | 15/28 [00:05<00:04, 2.96it/s]\n 57%|█████▋ | 16/28 [00:05<00:04, 2.96it/s]\n 61%|██████ | 17/28 [00:05<00:03, 2.96it/s]\n 64%|██████▍ | 18/28 [00:06<00:03, 2.96it/s]\n 68%|██████▊ | 19/28 [00:06<00:03, 2.96it/s]\n 71%|███████▏ | 20/28 [00:06<00:02, 2.95it/s]\n 75%|███████▌ | 21/28 [00:07<00:02, 2.95it/s]\n 79%|███████▊ | 22/28 [00:07<00:02, 2.95it/s]\n 82%|████████▏ | 23/28 [00:07<00:01, 2.95it/s]\n 86%|████████▌ | 24/28 [00:08<00:01, 2.95it/s]\n 89%|████████▉ | 25/28 [00:08<00:01, 2.95it/s]\n 93%|█████████▎| 26/28 [00:08<00:00, 2.95it/s]\n 96%|█████████▋| 27/28 [00:09<00:00, 2.95it/s]\n100%|██████████| 28/28 [00:09<00:00, 2.95it/s]\n100%|██████████| 28/28 [00:09<00:00, 2.97it/s]", "metrics": { "predict_time": 11.541233936, "total_time": 11.552425 }, "output": [ "https://replicate.delivery/yhqm/tm0ZfW7JPu2BU6kpqEjPhKW6mvvaHyaZQJYO00pfePuYRVLnA/out-0.webp" ], "started_at": "2024-10-11T10:04:16.536191Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/8xyp99sz1nrm60cjfc4vzhga9m", "cancel": "https://api.replicate.com/v1/predictions/8xyp99sz1nrm60cjfc4vzhga9m/cancel" }, "version": "5e6178aa59d0653f3a649ab6cdd0603e524d5a7e57401c29f6c9ebe13e84c2f9" }Generated inUsing seed: 51996 Prompt: A photo of a CYBERCAB with one door open, in San Francisco [!] txt2img mode Using dev model free=7544279883776 Downloading weights 2024-10-11T10:04:16Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpkvm_rqao/weights url=https://replicate.delivery/yhqm/zer7jDTdcWTlIKo2lXz1qLGHj2piBy1BdaMerWksKLoEkqlTA/trained_model.tar 2024-10-11T10:04:17Z | INFO | [ Complete ] dest=/tmp/tmpkvm_rqao/weights size="172 MB" total_elapsed=1.025s url=https://replicate.delivery/yhqm/zer7jDTdcWTlIKo2lXz1qLGHj2piBy1BdaMerWksKLoEkqlTA/trained_model.tar Downloaded weights in 1.05s Loaded LoRAs in 1.78s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:09, 2.95it/s] 7%|▋ | 2/28 [00:00<00:07, 3.29it/s] 11%|█ | 3/28 [00:00<00:07, 3.13it/s] 14%|█▍ | 4/28 [00:01<00:07, 3.06it/s] 18%|█▊ | 5/28 [00:01<00:07, 3.02it/s] 21%|██▏ | 6/28 [00:01<00:07, 3.00it/s] 25%|██▌ | 7/28 [00:02<00:07, 2.98it/s] 29%|██▊ | 8/28 [00:02<00:06, 2.97it/s] 32%|███▏ | 9/28 [00:02<00:06, 2.97it/s] 36%|███▌ | 10/28 [00:03<00:06, 2.96it/s] 39%|███▉ | 11/28 [00:03<00:05, 2.96it/s] 43%|████▎ | 12/28 [00:04<00:05, 2.96it/s] 46%|████▋ | 13/28 [00:04<00:05, 2.96it/s] 50%|█████ | 14/28 [00:04<00:04, 2.96it/s] 54%|█████▎ | 15/28 [00:05<00:04, 2.96it/s] 57%|█████▋ | 16/28 [00:05<00:04, 2.96it/s] 61%|██████ | 17/28 [00:05<00:03, 2.96it/s] 64%|██████▍ | 18/28 [00:06<00:03, 2.96it/s] 68%|██████▊ | 19/28 [00:06<00:03, 2.96it/s] 71%|███████▏ | 20/28 [00:06<00:02, 2.95it/s] 75%|███████▌ | 21/28 [00:07<00:02, 2.95it/s] 79%|███████▊ | 22/28 [00:07<00:02, 2.95it/s] 82%|████████▏ | 23/28 [00:07<00:01, 2.95it/s] 86%|████████▌ | 24/28 [00:08<00:01, 2.95it/s] 89%|████████▉ | 25/28 [00:08<00:01, 2.95it/s] 93%|█████████▎| 26/28 [00:08<00:00, 2.95it/s] 96%|█████████▋| 27/28 [00:09<00:00, 2.95it/s] 100%|██████████| 28/28 [00:09<00:00, 2.95it/s] 100%|██████████| 28/28 [00:09<00:00, 2.97it/s]
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