doriandarko / lcm-hiroshinagai
A smaller cuter, but lower quality version of my SDXL Hiroshi Nagai model
- Public
- 97 runs
-
L40S
Prediction
doriandarko/lcm-hiroshinagai:b43c25e9643af233e1258c839b6c6726504cbc25a1843ff80d83d911b8c99faaIDrvfyredbs74pkb7xsyhv5dtb34StatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- seed
- 1989
- width
- 1024
- height
- 1024
- prompt
- In the style of TOK, a car in the countryside
- scheduler
- LCM
- lora_scale
- 0.6
- num_outputs
- 4
- guidance_scale
- 2
- apply_watermark
- negative_prompt
- black and white, ugly,
- prompt_strength
- 0.8
- num_inference_steps
- 6
{ "seed": 1989, "width": 1024, "height": 1024, "prompt": "In the style of TOK, a car in the countryside", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "black and white, ugly, ", "prompt_strength": 0.8, "num_inference_steps": 6 }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 doriandarko/lcm-hiroshinagai using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "doriandarko/lcm-hiroshinagai:b43c25e9643af233e1258c839b6c6726504cbc25a1843ff80d83d911b8c99faa", { input: { seed: 1989, width: 1024, height: 1024, prompt: "In the style of TOK, a car in the countryside", scheduler: "LCM", lora_scale: 0.6, num_outputs: 4, guidance_scale: 2, apply_watermark: true, negative_prompt: "black and white, ugly, ", prompt_strength: 0.8, num_inference_steps: 6 } } ); // 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 doriandarko/lcm-hiroshinagai using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "doriandarko/lcm-hiroshinagai:b43c25e9643af233e1258c839b6c6726504cbc25a1843ff80d83d911b8c99faa", input={ "seed": 1989, "width": 1024, "height": 1024, "prompt": "In the style of TOK, a car in the countryside", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 2, "apply_watermark": True, "negative_prompt": "black and white, ugly, ", "prompt_strength": 0.8, "num_inference_steps": 6 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run doriandarko/lcm-hiroshinagai 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": "doriandarko/lcm-hiroshinagai:b43c25e9643af233e1258c839b6c6726504cbc25a1843ff80d83d911b8c99faa", "input": { "seed": 1989, "width": 1024, "height": 1024, "prompt": "In the style of TOK, a car in the countryside", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "black and white, ugly, ", "prompt_strength": 0.8, "num_inference_steps": 6 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-15T05:19:27.124220Z", "created_at": "2023-11-15T05:19:11.798636Z", "data_removed": false, "error": null, "id": "rvfyredbs74pkb7xsyhv5dtb34", "input": { "seed": 1989, "width": 1024, "height": 1024, "prompt": "In the style of TOK, a car in the countryside", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "black and white, ugly, ", "prompt_strength": 0.8, "num_inference_steps": 6 }, "logs": "Using seed: 1989\nskipping loading .. weights already loaded\nPrompt: In the style of <s0><s1>, a car in the countryside\ntxt2img mode\nThe config attributes {'skip_prk_steps': True} were passed to LCMScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n 0%| | 0/6 [00:00<?, ?it/s]\n 17%|█▋ | 1/6 [00:00<00:04, 1.02it/s]\n 33%|███▎ | 2/6 [00:01<00:03, 1.02it/s]\n 50%|█████ | 3/6 [00:02<00:02, 1.02it/s]\n 67%|██████▋ | 4/6 [00:03<00:01, 1.01it/s]\n 83%|████████▎ | 5/6 [00:04<00:00, 1.01it/s]\n100%|██████████| 6/6 [00:05<00:00, 1.01it/s]\n100%|██████████| 6/6 [00:05<00:00, 1.01it/s]", "metrics": { "predict_time": 13.080076, "total_time": 15.325584 }, "output": [ "https://replicate.delivery/pbxt/CWhnp689hh5AKZvfyxNKFJzarCFQxOfq0VpvqWewzJI52AxjA/out-0.png", "https://replicate.delivery/pbxt/fu5oAgiiHd10bqnWA49QsvEfmux3vyDGogTaLCZH14kdbg4RA/out-1.png", "https://replicate.delivery/pbxt/QJSZ0Dbn9pbXOt8qrDItHsfOtK9GMfzVel2kUydueZf1bDEPC/out-2.png", "https://replicate.delivery/pbxt/UQ9dsOn0gfyJY6FkMN4gQbNz7vf7BpwhKla7KGikvJ4e2AxjA/out-3.png" ], "started_at": "2023-11-15T05:19:14.044144Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/rvfyredbs74pkb7xsyhv5dtb34", "cancel": "https://api.replicate.com/v1/predictions/rvfyredbs74pkb7xsyhv5dtb34/cancel" }, "version": "b43c25e9643af233e1258c839b6c6726504cbc25a1843ff80d83d911b8c99faa" }Generated inUsing seed: 1989 skipping loading .. weights already loaded Prompt: In the style of <s0><s1>, a car in the countryside txt2img mode The config attributes {'skip_prk_steps': True} were passed to LCMScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file. 0%| | 0/6 [00:00<?, ?it/s] 17%|█▋ | 1/6 [00:00<00:04, 1.02it/s] 33%|███▎ | 2/6 [00:01<00:03, 1.02it/s] 50%|█████ | 3/6 [00:02<00:02, 1.02it/s] 67%|██████▋ | 4/6 [00:03<00:01, 1.01it/s] 83%|████████▎ | 5/6 [00:04<00:00, 1.01it/s] 100%|██████████| 6/6 [00:05<00:00, 1.01it/s] 100%|██████████| 6/6 [00:05<00:00, 1.01it/s]Prediction
doriandarko/lcm-hiroshinagai:b43c25e9643af233e1258c839b6c6726504cbc25a1843ff80d83d911b8c99faaIDpbnkr4tbfqd3pahwxyfv3ab24aStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- In the style of TOK, a car in the countryside
- scheduler
- LCM
- lora_scale
- 0.6
- num_outputs
- 4
- guidance_scale
- 2
- apply_watermark
- negative_prompt
- black and white, ugly,
- prompt_strength
- 0.8
- num_inference_steps
- 6
{ "width": 1024, "height": 1024, "prompt": "In the style of TOK, a car in the countryside", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "black and white, ugly, ", "prompt_strength": 0.8, "num_inference_steps": 6 }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 doriandarko/lcm-hiroshinagai using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "doriandarko/lcm-hiroshinagai:b43c25e9643af233e1258c839b6c6726504cbc25a1843ff80d83d911b8c99faa", { input: { width: 1024, height: 1024, prompt: "In the style of TOK, a car in the countryside", scheduler: "LCM", lora_scale: 0.6, num_outputs: 4, guidance_scale: 2, apply_watermark: true, negative_prompt: "black and white, ugly, ", prompt_strength: 0.8, num_inference_steps: 6 } } ); // 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 doriandarko/lcm-hiroshinagai using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "doriandarko/lcm-hiroshinagai:b43c25e9643af233e1258c839b6c6726504cbc25a1843ff80d83d911b8c99faa", input={ "width": 1024, "height": 1024, "prompt": "In the style of TOK, a car in the countryside", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 2, "apply_watermark": True, "negative_prompt": "black and white, ugly, ", "prompt_strength": 0.8, "num_inference_steps": 6 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run doriandarko/lcm-hiroshinagai 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": "doriandarko/lcm-hiroshinagai:b43c25e9643af233e1258c839b6c6726504cbc25a1843ff80d83d911b8c99faa", "input": { "width": 1024, "height": 1024, "prompt": "In the style of TOK, a car in the countryside", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "black and white, ugly, ", "prompt_strength": 0.8, "num_inference_steps": 6 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-15T05:16:34.537473Z", "created_at": "2023-11-15T05:16:18.166860Z", "data_removed": false, "error": null, "id": "pbnkr4tbfqd3pahwxyfv3ab24a", "input": { "width": 1024, "height": 1024, "prompt": "In the style of TOK, a car in the countryside", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "black and white, ugly, ", "prompt_strength": 0.8, "num_inference_steps": 6 }, "logs": "Using seed: 48493\nEnsuring enough disk space...\nFree disk space: 1429398622208\nDownloading weights: https://replicate.delivery/pbxt/2qPgVBQfv02WJapYb0CrvfE0tEPGSWInWTo3Of2QTKDZZAxjA/trained_model.tar\nb'Downloaded 186 MB bytes in 0.660s (282 MB/s)\\nExtracted 186 MB in 0.065s (2.9 GB/s)\\n'\nDownloaded weights in 0.9539430141448975 seconds\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: In the style of <s0><s1>, a car in the countryside\ntxt2img mode\nThe config attributes {'skip_prk_steps': True} were passed to LCMScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n 0%| | 0/6 [00:00<?, ?it/s]/root/.pyenv/versions/3.10.13/lib/python3.10/site-packages/diffusers/models/attention_processor.py:1821: FutureWarning: `LoRAAttnProcessor2_0` is deprecated and will be removed in version 0.26.0. Make sure use AttnProcessor2_0 instead by settingLoRA layers to `self.{to_q,to_k,to_v,to_out[0]}.lora_layer` respectively. This will be done automatically when using `LoraLoaderMixin.load_lora_weights`\ndeprecate(\n 17%|█▋ | 1/6 [00:01<00:05, 1.13s/it]\n 33%|███▎ | 2/6 [00:02<00:04, 1.04s/it]\n 50%|█████ | 3/6 [00:03<00:03, 1.02s/it]\n 67%|██████▋ | 4/6 [00:04<00:02, 1.01s/it]\n 83%|████████▎ | 5/6 [00:05<00:00, 1.00it/s]\n100%|██████████| 6/6 [00:06<00:00, 1.00it/s]\n100%|██████████| 6/6 [00:06<00:00, 1.01s/it]", "metrics": { "predict_time": 14.691208, "total_time": 16.370613 }, "output": [ "https://replicate.delivery/pbxt/90BuEtogj0qtJJhLnL7S1QDh0Yc2VoKWTIU4y1e9fUzvYg4RA/out-0.png", "https://replicate.delivery/pbxt/bJnt9cRo1trePqWQnmrTMLip6XCDG3PU1nIkfQ8TyT4xYg4RA/out-1.png", "https://replicate.delivery/pbxt/222CgQeIeImZB0OqmH5JTLjS5F8oW5NDfit1vT0UlOljxAxjA/out-2.png", "https://replicate.delivery/pbxt/WZzbeAUZbQWDQCGPzppipFABshrtEEcrmVcWSaBH24HZMQ8IA/out-3.png" ], "started_at": "2023-11-15T05:16:19.846265Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/pbnkr4tbfqd3pahwxyfv3ab24a", "cancel": "https://api.replicate.com/v1/predictions/pbnkr4tbfqd3pahwxyfv3ab24a/cancel" }, "version": "b43c25e9643af233e1258c839b6c6726504cbc25a1843ff80d83d911b8c99faa" }Generated inUsing seed: 48493 Ensuring enough disk space... Free disk space: 1429398622208 Downloading weights: https://replicate.delivery/pbxt/2qPgVBQfv02WJapYb0CrvfE0tEPGSWInWTo3Of2QTKDZZAxjA/trained_model.tar b'Downloaded 186 MB bytes in 0.660s (282 MB/s)\nExtracted 186 MB in 0.065s (2.9 GB/s)\n' Downloaded weights in 0.9539430141448975 seconds Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: In the style of <s0><s1>, a car in the countryside txt2img mode The config attributes {'skip_prk_steps': True} were passed to LCMScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file. 0%| | 0/6 [00:00<?, ?it/s]/root/.pyenv/versions/3.10.13/lib/python3.10/site-packages/diffusers/models/attention_processor.py:1821: FutureWarning: `LoRAAttnProcessor2_0` is deprecated and will be removed in version 0.26.0. Make sure use AttnProcessor2_0 instead by settingLoRA layers to `self.{to_q,to_k,to_v,to_out[0]}.lora_layer` respectively. This will be done automatically when using `LoraLoaderMixin.load_lora_weights` deprecate( 17%|█▋ | 1/6 [00:01<00:05, 1.13s/it] 33%|███▎ | 2/6 [00:02<00:04, 1.04s/it] 50%|█████ | 3/6 [00:03<00:03, 1.02s/it] 67%|██████▋ | 4/6 [00:04<00:02, 1.01s/it] 83%|████████▎ | 5/6 [00:05<00:00, 1.00it/s] 100%|██████████| 6/6 [00:06<00:00, 1.00it/s] 100%|██████████| 6/6 [00:06<00:00, 1.01s/it]Prediction
doriandarko/lcm-hiroshinagai:b43c25e9643af233e1258c839b6c6726504cbc25a1843ff80d83d911b8c99faaID7bf2dkdbrkv2q374bxvmoons6aStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- In the style of TOK. A mid-century modern house with a pool, surrounded by palm trees
- scheduler
- LCM
- lora_scale
- 0.6
- num_outputs
- 4
- guidance_scale
- 2
- apply_watermark
- negative_prompt
- Gothic, Medieval, Abstract, Futuristic, Rustic, Victorian, Graffiti, Fantasy, Horror, Industrial, Cubism, Impressionism, Surrealism, Baroque, Renaissance, Expressionism, Pop-art, Dystopian, Steampunk, Cyberpunk, Ugly, Bad proportion, Distorted, Cluttered, Chaotic, Mismatched, Overcrowded, Imbalanced, Inharmonious, Disproportionate, Unpleasant, Grungy, Messy, Unrefined, Crude, Grotesque, Disarray, Jumbled, Haphazard, Unsymmetrical
- prompt_strength
- 0.8
- num_inference_steps
- 6
{ "width": 1024, "height": 1024, "prompt": "In the style of TOK. A mid-century modern house with a pool, surrounded by palm trees ", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "Gothic, Medieval, Abstract, Futuristic, Rustic, Victorian, Graffiti, Fantasy, Horror, Industrial, Cubism, Impressionism, Surrealism, Baroque, Renaissance, Expressionism, Pop-art, Dystopian, Steampunk, Cyberpunk, Ugly, Bad proportion, Distorted, Cluttered, Chaotic, Mismatched, Overcrowded, Imbalanced, Inharmonious, Disproportionate, Unpleasant, Grungy, Messy, Unrefined, Crude, Grotesque, Disarray, Jumbled, Haphazard, Unsymmetrical\n", "prompt_strength": 0.8, "num_inference_steps": 6 }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 doriandarko/lcm-hiroshinagai using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "doriandarko/lcm-hiroshinagai:b43c25e9643af233e1258c839b6c6726504cbc25a1843ff80d83d911b8c99faa", { input: { width: 1024, height: 1024, prompt: "In the style of TOK. A mid-century modern house with a pool, surrounded by palm trees ", scheduler: "LCM", lora_scale: 0.6, num_outputs: 4, guidance_scale: 2, apply_watermark: true, negative_prompt: "Gothic, Medieval, Abstract, Futuristic, Rustic, Victorian, Graffiti, Fantasy, Horror, Industrial, Cubism, Impressionism, Surrealism, Baroque, Renaissance, Expressionism, Pop-art, Dystopian, Steampunk, Cyberpunk, Ugly, Bad proportion, Distorted, Cluttered, Chaotic, Mismatched, Overcrowded, Imbalanced, Inharmonious, Disproportionate, Unpleasant, Grungy, Messy, Unrefined, Crude, Grotesque, Disarray, Jumbled, Haphazard, Unsymmetrical\n", prompt_strength: 0.8, num_inference_steps: 6 } } ); // 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 doriandarko/lcm-hiroshinagai using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "doriandarko/lcm-hiroshinagai:b43c25e9643af233e1258c839b6c6726504cbc25a1843ff80d83d911b8c99faa", input={ "width": 1024, "height": 1024, "prompt": "In the style of TOK. A mid-century modern house with a pool, surrounded by palm trees ", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 2, "apply_watermark": True, "negative_prompt": "Gothic, Medieval, Abstract, Futuristic, Rustic, Victorian, Graffiti, Fantasy, Horror, Industrial, Cubism, Impressionism, Surrealism, Baroque, Renaissance, Expressionism, Pop-art, Dystopian, Steampunk, Cyberpunk, Ugly, Bad proportion, Distorted, Cluttered, Chaotic, Mismatched, Overcrowded, Imbalanced, Inharmonious, Disproportionate, Unpleasant, Grungy, Messy, Unrefined, Crude, Grotesque, Disarray, Jumbled, Haphazard, Unsymmetrical\n", "prompt_strength": 0.8, "num_inference_steps": 6 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run doriandarko/lcm-hiroshinagai 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": "doriandarko/lcm-hiroshinagai:b43c25e9643af233e1258c839b6c6726504cbc25a1843ff80d83d911b8c99faa", "input": { "width": 1024, "height": 1024, "prompt": "In the style of TOK. A mid-century modern house with a pool, surrounded by palm trees ", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "Gothic, Medieval, Abstract, Futuristic, Rustic, Victorian, Graffiti, Fantasy, Horror, Industrial, Cubism, Impressionism, Surrealism, Baroque, Renaissance, Expressionism, Pop-art, Dystopian, Steampunk, Cyberpunk, Ugly, Bad proportion, Distorted, Cluttered, Chaotic, Mismatched, Overcrowded, Imbalanced, Inharmonious, Disproportionate, Unpleasant, Grungy, Messy, Unrefined, Crude, Grotesque, Disarray, Jumbled, Haphazard, Unsymmetrical\\n", "prompt_strength": 0.8, "num_inference_steps": 6 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-15T05:15:00.408645Z", "created_at": "2023-11-15T05:14:43.142398Z", "data_removed": false, "error": null, "id": "7bf2dkdbrkv2q374bxvmoons6a", "input": { "width": 1024, "height": 1024, "prompt": "In the style of TOK. A mid-century modern house with a pool, surrounded by palm trees ", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "Gothic, Medieval, Abstract, Futuristic, Rustic, Victorian, Graffiti, Fantasy, Horror, Industrial, Cubism, Impressionism, Surrealism, Baroque, Renaissance, Expressionism, Pop-art, Dystopian, Steampunk, Cyberpunk, Ugly, Bad proportion, Distorted, Cluttered, Chaotic, Mismatched, Overcrowded, Imbalanced, Inharmonious, Disproportionate, Unpleasant, Grungy, Messy, Unrefined, Crude, Grotesque, Disarray, Jumbled, Haphazard, Unsymmetrical\n", "prompt_strength": 0.8, "num_inference_steps": 6 }, "logs": "Using seed: 5739\nEnsuring enough disk space...\nFree disk space: 1456477806592\nDownloading weights: https://replicate.delivery/pbxt/2qPgVBQfv02WJapYb0CrvfE0tEPGSWInWTo3Of2QTKDZZAxjA/trained_model.tar\nb'Downloaded 186 MB bytes in 0.989s (188 MB/s)\\nExtracted 186 MB in 0.057s (3.3 GB/s)\\n'\nDownloaded weights in 1.2983520030975342 seconds\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: In the style of <s0><s1>. A mid-century modern house with a pool, surrounded by palm trees\ntxt2img mode\nThe config attributes {'skip_prk_steps': True} were passed to LCMScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n 0%| | 0/6 [00:00<?, ?it/s]/root/.pyenv/versions/3.10.13/lib/python3.10/site-packages/diffusers/models/attention_processor.py:1821: FutureWarning: `LoRAAttnProcessor2_0` is deprecated and will be removed in version 0.26.0. Make sure use AttnProcessor2_0 instead by settingLoRA layers to `self.{to_q,to_k,to_v,to_out[0]}.lora_layer` respectively. This will be done automatically when using `LoraLoaderMixin.load_lora_weights`\ndeprecate(\n 17%|█▋ | 1/6 [00:01<00:05, 1.14s/it]\n 33%|███▎ | 2/6 [00:02<00:04, 1.06s/it]\n 50%|█████ | 3/6 [00:03<00:03, 1.03s/it]\n 67%|██████▋ | 4/6 [00:04<00:02, 1.02s/it]\n 83%|████████▎ | 5/6 [00:05<00:01, 1.01s/it]\n100%|██████████| 6/6 [00:06<00:00, 1.01s/it]\n100%|██████████| 6/6 [00:06<00:00, 1.02s/it]", "metrics": { "predict_time": 15.165352, "total_time": 17.266247 }, "output": [ "https://replicate.delivery/pbxt/XejekARL6gmq6EMG08QYKPn0XsfZenw9v8oGhVlXPdQHdBiHB/out-0.png", "https://replicate.delivery/pbxt/42yML1nyvz6XK9JOyRnbGsHu1NhYFxbRleFIB8uHViRpLQ8IA/out-1.png", "https://replicate.delivery/pbxt/ETzexSZM3lUWR6byZICrlTIz71iP00IoocLpwYePfXOmuAxjA/out-2.png", "https://replicate.delivery/pbxt/Ukgl1mSWC0qtJ9ut0mVLfN30h0k3shYj9WGSe0UlWbNUXg4RA/out-3.png" ], "started_at": "2023-11-15T05:14:45.243293Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/7bf2dkdbrkv2q374bxvmoons6a", "cancel": "https://api.replicate.com/v1/predictions/7bf2dkdbrkv2q374bxvmoons6a/cancel" }, "version": "b43c25e9643af233e1258c839b6c6726504cbc25a1843ff80d83d911b8c99faa" }Generated inUsing seed: 5739 Ensuring enough disk space... Free disk space: 1456477806592 Downloading weights: https://replicate.delivery/pbxt/2qPgVBQfv02WJapYb0CrvfE0tEPGSWInWTo3Of2QTKDZZAxjA/trained_model.tar b'Downloaded 186 MB bytes in 0.989s (188 MB/s)\nExtracted 186 MB in 0.057s (3.3 GB/s)\n' Downloaded weights in 1.2983520030975342 seconds Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: In the style of <s0><s1>. A mid-century modern house with a pool, surrounded by palm trees txt2img mode The config attributes {'skip_prk_steps': True} were passed to LCMScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file. 0%| | 0/6 [00:00<?, ?it/s]/root/.pyenv/versions/3.10.13/lib/python3.10/site-packages/diffusers/models/attention_processor.py:1821: FutureWarning: `LoRAAttnProcessor2_0` is deprecated and will be removed in version 0.26.0. Make sure use AttnProcessor2_0 instead by settingLoRA layers to `self.{to_q,to_k,to_v,to_out[0]}.lora_layer` respectively. This will be done automatically when using `LoraLoaderMixin.load_lora_weights` deprecate( 17%|█▋ | 1/6 [00:01<00:05, 1.14s/it] 33%|███▎ | 2/6 [00:02<00:04, 1.06s/it] 50%|█████ | 3/6 [00:03<00:03, 1.03s/it] 67%|██████▋ | 4/6 [00:04<00:02, 1.02s/it] 83%|████████▎ | 5/6 [00:05<00:01, 1.01s/it] 100%|██████████| 6/6 [00:06<00:00, 1.01s/it] 100%|██████████| 6/6 [00:06<00:00, 1.02s/it]
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