tezzarida
/
aram
fine tuned flux+lora model with my face
- Public
- 139 runs
-
H100
Prediction
tezzarida/aram:eb07a016ff7cb61e8dc9eedbafb9a7ee5e3f62a12bfd1f40c961349bd86ea4c4ID3ka8f42y8nrm00chkb38t3ndb4StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a photo of aram as a masculine man, dressed in white polo,blue liger linen pants,silver necklace,standing straight,hands relaxed,confident stance, in a long street in mountain overlook, with the horizon stretching out behind you lit by the early morning sun,cinematic lighting
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 2
- output_quality
- 100
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a photo of aram as a masculine man, dressed in white polo,blue liger linen pants,silver necklace,standing straight,hands relaxed,confident stance, in a long street in mountain overlook, with the horizon stretching out behind you lit by the early morning sun,cinematic lighting ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 2, "output_quality": 100, "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 tezzarida/aram using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "tezzarida/aram:eb07a016ff7cb61e8dc9eedbafb9a7ee5e3f62a12bfd1f40c961349bd86ea4c4", { input: { model: "dev", prompt: "a photo of aram as a masculine man, dressed in white polo,blue liger linen pants,silver necklace,standing straight,hands relaxed,confident stance, in a long street in mountain overlook, with the horizon stretching out behind you lit by the early morning sun,cinematic lighting ", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 2, output_quality: 100, 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 tezzarida/aram using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "tezzarida/aram:eb07a016ff7cb61e8dc9eedbafb9a7ee5e3f62a12bfd1f40c961349bd86ea4c4", input={ "model": "dev", "prompt": "a photo of aram as a masculine man, dressed in white polo,blue liger linen pants,silver necklace,standing straight,hands relaxed,confident stance, in a long street in mountain overlook, with the horizon stretching out behind you lit by the early morning sun,cinematic lighting ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 2, "output_quality": 100, "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 tezzarida/aram 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": "eb07a016ff7cb61e8dc9eedbafb9a7ee5e3f62a12bfd1f40c961349bd86ea4c4", "input": { "model": "dev", "prompt": "a photo of aram as a masculine man, dressed in white polo,blue liger linen pants,silver necklace,standing straight,hands relaxed,confident stance, in a long street in mountain overlook, with the horizon stretching out behind you lit by the early morning sun,cinematic lighting ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 2, "output_quality": 100, "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": "2024-08-28T20:56:38.294796Z", "created_at": "2024-08-28T20:56:17.221000Z", "data_removed": false, "error": null, "id": "3ka8f42y8nrm00chkb38t3ndb4", "input": { "model": "dev", "prompt": "a photo of aram as a masculine man, dressed in white polo,blue liger linen pants,silver necklace,standing straight,hands relaxed,confident stance, in a long street in mountain overlook, with the horizon stretching out behind you lit by the early morning sun,cinematic lighting ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 2, "output_quality": 100, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 61223\nPrompt: a photo of aram as a masculine man, dressed in white polo,blue liger linen pants,silver necklace,standing straight,hands relaxed,confident stance, in a long street in mountain overlook, with the horizon stretching out behind you lit by the early morning sun,cinematic lighting\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 12.94s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.71it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.26it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.98it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.86it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.80it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.77it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.74it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.73it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.72it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.71it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.71it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.70it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.70it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.70it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.70it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.70it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.70it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.70it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.70it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.70it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.70it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.70it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.70it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.70it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.70it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.70it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.70it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.70it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.73it/s]", "metrics": { "predict_time": 21.066871899, "total_time": 21.073796 }, "output": [ "https://replicate.delivery/yhqm/TJEkp9vSPn5ULhKq1Cckv6N0Ga5hCgBCtnhf1sZW1gADCqrJA/out-0.webp" ], "started_at": "2024-08-28T20:56:17.227924Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/3ka8f42y8nrm00chkb38t3ndb4", "cancel": "https://api.replicate.com/v1/predictions/3ka8f42y8nrm00chkb38t3ndb4/cancel" }, "version": "eb07a016ff7cb61e8dc9eedbafb9a7ee5e3f62a12bfd1f40c961349bd86ea4c4" }Generated inUsing seed: 61223 Prompt: a photo of aram as a masculine man, dressed in white polo,blue liger linen pants,silver necklace,standing straight,hands relaxed,confident stance, in a long street in mountain overlook, with the horizon stretching out behind you lit by the early morning sun,cinematic lighting txt2img mode Using dev model Loaded LoRAs in 12.94s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.71it/s] 7%|▋ | 2/28 [00:00<00:06, 4.26it/s] 11%|█ | 3/28 [00:00<00:06, 3.98it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.86it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.80it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.77it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.74it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.73it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.72it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.71it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.71it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.70it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.70it/s] 50%|█████ | 14/28 [00:03<00:03, 3.70it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.70it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.70it/s] 61%|██████ | 17/28 [00:04<00:02, 3.70it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.70it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.70it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.70it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.70it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.70it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.70it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.70it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.70it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.70it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.70it/s] 100%|██████████| 28/28 [00:07<00:00, 3.70it/s] 100%|██████████| 28/28 [00:07<00:00, 3.73it/s]Prediction
tezzarida/aram:eb07a016ff7cb61e8dc9eedbafb9a7ee5e3f62a12bfd1f40c961349bd86ea4c4IDvr4pn08x9srm00chkb7vz393jrStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a photo of aram as a masculine man, dressed in A high-quality, fitted outdoor jacket in navy or burgundy over a thermal turtleneck sweater,standing straight,hands relaxed,confident stance, in a long street in mountain overlook, with the horizon stretching out behind you lit by the early morning sun,cinematic lighting
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 2
- output_quality
- 100
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a photo of aram as a masculine man, dressed in A high-quality, fitted outdoor jacket in navy or burgundy over a thermal turtleneck sweater,standing straight,hands relaxed,confident stance, in a long street in mountain overlook, with the horizon stretching out behind you lit by the early morning sun,cinematic lighting ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 2, "output_quality": 100, "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 tezzarida/aram using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "tezzarida/aram:eb07a016ff7cb61e8dc9eedbafb9a7ee5e3f62a12bfd1f40c961349bd86ea4c4", { input: { model: "dev", prompt: "a photo of aram as a masculine man, dressed in A high-quality, fitted outdoor jacket in navy or burgundy over a thermal turtleneck sweater,standing straight,hands relaxed,confident stance, in a long street in mountain overlook, with the horizon stretching out behind you lit by the early morning sun,cinematic lighting ", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 2, output_quality: 100, 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 tezzarida/aram using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "tezzarida/aram:eb07a016ff7cb61e8dc9eedbafb9a7ee5e3f62a12bfd1f40c961349bd86ea4c4", input={ "model": "dev", "prompt": "a photo of aram as a masculine man, dressed in A high-quality, fitted outdoor jacket in navy or burgundy over a thermal turtleneck sweater,standing straight,hands relaxed,confident stance, in a long street in mountain overlook, with the horizon stretching out behind you lit by the early morning sun,cinematic lighting ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 2, "output_quality": 100, "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 tezzarida/aram 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": "eb07a016ff7cb61e8dc9eedbafb9a7ee5e3f62a12bfd1f40c961349bd86ea4c4", "input": { "model": "dev", "prompt": "a photo of aram as a masculine man, dressed in A high-quality, fitted outdoor jacket in navy or burgundy over a thermal turtleneck sweater,standing straight,hands relaxed,confident stance, in a long street in mountain overlook, with the horizon stretching out behind you lit by the early morning sun,cinematic lighting ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 2, "output_quality": 100, "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": "2024-08-28T21:06:37.455891Z", "created_at": "2024-08-28T21:05:50.414000Z", "data_removed": false, "error": null, "id": "vr4pn08x9srm00chkb7vz393jr", "input": { "model": "dev", "prompt": "a photo of aram as a masculine man, dressed in A high-quality, fitted outdoor jacket in navy or burgundy over a thermal turtleneck sweater,standing straight,hands relaxed,confident stance, in a long street in mountain overlook, with the horizon stretching out behind you lit by the early morning sun,cinematic lighting ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 2, "output_quality": 100, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 38277\nPrompt: a photo of aram as a masculine man, dressed in A high-quality, fitted outdoor jacket in navy or burgundy over a thermal turtleneck sweater,standing straight,hands relaxed,confident stance, in a long street in mountain overlook, with the horizon stretching out behind you lit by the early morning sun,cinematic lighting\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 33.83s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.71it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.26it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.99it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.87it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.81it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.77it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.75it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.74it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.73it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.72it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.71it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.71it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.71it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.71it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.71it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.71it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.71it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.71it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.71it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.71it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.71it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.71it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.71it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.70it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.70it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.70it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.71it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.70it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.73it/s]", "metrics": { "predict_time": 41.905873897, "total_time": 47.041891 }, "output": [ "https://replicate.delivery/yhqm/445YsfMDikUxfEaG7fvICUOl9gsZzhdtOkDmozFT6fq11QdNB/out-0.webp" ], "started_at": "2024-08-28T21:05:55.550017Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/vr4pn08x9srm00chkb7vz393jr", "cancel": "https://api.replicate.com/v1/predictions/vr4pn08x9srm00chkb7vz393jr/cancel" }, "version": "eb07a016ff7cb61e8dc9eedbafb9a7ee5e3f62a12bfd1f40c961349bd86ea4c4" }Generated inUsing seed: 38277 Prompt: a photo of aram as a masculine man, dressed in A high-quality, fitted outdoor jacket in navy or burgundy over a thermal turtleneck sweater,standing straight,hands relaxed,confident stance, in a long street in mountain overlook, with the horizon stretching out behind you lit by the early morning sun,cinematic lighting txt2img mode Using dev model Loaded LoRAs in 33.83s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.71it/s] 7%|▋ | 2/28 [00:00<00:06, 4.26it/s] 11%|█ | 3/28 [00:00<00:06, 3.99it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.87it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.81it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.77it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.75it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.74it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.73it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.72it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.71it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.71it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.71it/s] 50%|█████ | 14/28 [00:03<00:03, 3.71it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.71it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.71it/s] 61%|██████ | 17/28 [00:04<00:02, 3.71it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.71it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.71it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.71it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.71it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.71it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.71it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.70it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.70it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.70it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.71it/s] 100%|██████████| 28/28 [00:07<00:00, 3.70it/s] 100%|██████████| 28/28 [00:07<00:00, 3.73it/s]
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