paulccote / old-school-3d-renders
Creates an image in the style of an old school 3D render. Prefix: "An old school 3D render of". Suffix: "in the style of 3DRNDR"
- Public
- 723 runs
-
H100
Prediction
paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8IDkvjn8k157xrm20cht9es63x9jwStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- An old school 3D render of a bonsai orchard in the style of 3DRNDR
- 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": "An old school 3D render of a bonsai orchard in the style of 3DRNDR", "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 paulccote/old-school-3d-renders using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8", { input: { model: "dev", prompt: "An old school 3D render of a bonsai orchard in the style of 3DRNDR", 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 paulccote/old-school-3d-renders using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8", input={ "model": "dev", "prompt": "An old school 3D render of a bonsai orchard in the style of 3DRNDR", "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 paulccote/old-school-3d-renders 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": "paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8", "input": { "model": "dev", "prompt": "An old school 3D render of a bonsai orchard in the style of 3DRNDR", "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": "2024-09-08T16:00:32.153120Z", "created_at": "2024-09-08T16:00:05.439000Z", "data_removed": false, "error": null, "id": "kvjn8k157xrm20cht9es63x9jw", "input": { "model": "dev", "prompt": "An old school 3D render of a bonsai orchard in the style of 3DRNDR", "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: 28001\nPrompt: An old school 3D render of a bonsai orchard in the style of 3DRNDR\n[!] txt2img mode\nUsing dev model\nfree=8000926588928\nDownloading weights\n2024-09-08T16:00:05Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmplnsrvlgl/weights url=https://replicate.delivery/yhqm/1rNm3e6AWvXFYKfaxei1079gqwbRdKNnJGrJhSvPFOeGtbrNB/trained_model.tar\n2024-09-08T16:00:07Z | INFO | [ Complete ] dest=/tmp/tmplnsrvlgl/weights size=\"172 MB\" total_elapsed=2.126s url=https://replicate.delivery/yhqm/1rNm3e6AWvXFYKfaxei1079gqwbRdKNnJGrJhSvPFOeGtbrNB/trained_model.tar\nDownloaded weights in 2.15s\nLoaded LoRAs in 18.80s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.79it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.29it/s]\n 11%|█ | 3/28 [00:00<00:06, 4.05it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.95it/s]\n 18%|█▊ | 5/28 [00:01<00:05, 3.90it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.86it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.84it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.83it/s]\n 32%|███▏ | 9/28 [00:02<00:04, 3.82it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.81it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.81it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.81it/s]\n 46%|████▋ | 13/28 [00:03<00:03, 3.80it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.80it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.80it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.80it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.80it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.80it/s]\n 68%|██████▊ | 19/28 [00:04<00:02, 3.80it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.80it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.80it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.80it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.80it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.80it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.80it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.80it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.80it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.80it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.83it/s]", "metrics": { "predict_time": 26.704627577, "total_time": 26.71412 }, "output": [ "https://replicate.delivery/yhqm/Sifczaj5qGVcMSZabxPiKEWHyAcavfS6wTkoEkp82Fofgv1mA/out-0.webp" ], "started_at": "2024-09-08T16:00:05.448492Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/kvjn8k157xrm20cht9es63x9jw", "cancel": "https://api.replicate.com/v1/predictions/kvjn8k157xrm20cht9es63x9jw/cancel" }, "version": "742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8" }Generated inUsing seed: 28001 Prompt: An old school 3D render of a bonsai orchard in the style of 3DRNDR [!] txt2img mode Using dev model free=8000926588928 Downloading weights 2024-09-08T16:00:05Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmplnsrvlgl/weights url=https://replicate.delivery/yhqm/1rNm3e6AWvXFYKfaxei1079gqwbRdKNnJGrJhSvPFOeGtbrNB/trained_model.tar 2024-09-08T16:00:07Z | INFO | [ Complete ] dest=/tmp/tmplnsrvlgl/weights size="172 MB" total_elapsed=2.126s url=https://replicate.delivery/yhqm/1rNm3e6AWvXFYKfaxei1079gqwbRdKNnJGrJhSvPFOeGtbrNB/trained_model.tar Downloaded weights in 2.15s Loaded LoRAs in 18.80s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.79it/s] 7%|▋ | 2/28 [00:00<00:06, 4.29it/s] 11%|█ | 3/28 [00:00<00:06, 4.05it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.95it/s] 18%|█▊ | 5/28 [00:01<00:05, 3.90it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.86it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.84it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.83it/s] 32%|███▏ | 9/28 [00:02<00:04, 3.82it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.81it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.81it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.81it/s] 46%|████▋ | 13/28 [00:03<00:03, 3.80it/s] 50%|█████ | 14/28 [00:03<00:03, 3.80it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.80it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.80it/s] 61%|██████ | 17/28 [00:04<00:02, 3.80it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.80it/s] 68%|██████▊ | 19/28 [00:04<00:02, 3.80it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.80it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.80it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.80it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.80it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.80it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.80it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.80it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.80it/s] 100%|██████████| 28/28 [00:07<00:00, 3.80it/s] 100%|██████████| 28/28 [00:07<00:00, 3.83it/s]Prediction
paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8ID8fabc79mrsrm60cht9gtsdthwrStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- An old school 3D render of a cozy rainforest cafe on a misty morning. A wooden deck extends into the lush, green canopy, dotted with rustic tables and chairs. Steaming coffee cups and tropical fruit platters rest on some tables, while hanging lanterns and string lights provide ambient illumination. Potted exotic plants decorate the space beneath a partial thatched roof. Mist swirls through surrounding trees, with a distant waterfall visible through the foliage. Colorful birds perch nearby, and a vintage espresso machine occupies one corner. Soft, diffused lighting creates a tranquil atmosphere, perfectly blending the cafe into its rainforest setting. In the style of 3DRNDR
- 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": "An old school 3D render of a cozy rainforest cafe on a misty morning. A wooden deck extends into the lush, green canopy, dotted with rustic tables and chairs. Steaming coffee cups and tropical fruit platters rest on some tables, while hanging lanterns and string lights provide ambient illumination. Potted exotic plants decorate the space beneath a partial thatched roof. Mist swirls through surrounding trees, with a distant waterfall visible through the foliage. Colorful birds perch nearby, and a vintage espresso machine occupies one corner. Soft, diffused lighting creates a tranquil atmosphere, perfectly blending the cafe into its rainforest setting. In the style of 3DRNDR", "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 paulccote/old-school-3d-renders using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8", { input: { model: "dev", prompt: "An old school 3D render of a cozy rainforest cafe on a misty morning. A wooden deck extends into the lush, green canopy, dotted with rustic tables and chairs. Steaming coffee cups and tropical fruit platters rest on some tables, while hanging lanterns and string lights provide ambient illumination. Potted exotic plants decorate the space beneath a partial thatched roof. Mist swirls through surrounding trees, with a distant waterfall visible through the foliage. Colorful birds perch nearby, and a vintage espresso machine occupies one corner. Soft, diffused lighting creates a tranquil atmosphere, perfectly blending the cafe into its rainforest setting. In the style of 3DRNDR", 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 paulccote/old-school-3d-renders using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8", input={ "model": "dev", "prompt": "An old school 3D render of a cozy rainforest cafe on a misty morning. A wooden deck extends into the lush, green canopy, dotted with rustic tables and chairs. Steaming coffee cups and tropical fruit platters rest on some tables, while hanging lanterns and string lights provide ambient illumination. Potted exotic plants decorate the space beneath a partial thatched roof. Mist swirls through surrounding trees, with a distant waterfall visible through the foliage. Colorful birds perch nearby, and a vintage espresso machine occupies one corner. Soft, diffused lighting creates a tranquil atmosphere, perfectly blending the cafe into its rainforest setting. In the style of 3DRNDR", "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 paulccote/old-school-3d-renders 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": "paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8", "input": { "model": "dev", "prompt": "An old school 3D render of a cozy rainforest cafe on a misty morning. A wooden deck extends into the lush, green canopy, dotted with rustic tables and chairs. Steaming coffee cups and tropical fruit platters rest on some tables, while hanging lanterns and string lights provide ambient illumination. Potted exotic plants decorate the space beneath a partial thatched roof. Mist swirls through surrounding trees, with a distant waterfall visible through the foliage. Colorful birds perch nearby, and a vintage espresso machine occupies one corner. Soft, diffused lighting creates a tranquil atmosphere, perfectly blending the cafe into its rainforest setting. In the style of 3DRNDR", "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": "2024-09-08T16:04:49.178646Z", "created_at": "2024-09-08T16:04:31.558000Z", "data_removed": false, "error": null, "id": "8fabc79mrsrm60cht9gtsdthwr", "input": { "model": "dev", "prompt": "An old school 3D render of a cozy rainforest cafe on a misty morning. A wooden deck extends into the lush, green canopy, dotted with rustic tables and chairs. Steaming coffee cups and tropical fruit platters rest on some tables, while hanging lanterns and string lights provide ambient illumination. Potted exotic plants decorate the space beneath a partial thatched roof. Mist swirls through surrounding trees, with a distant waterfall visible through the foliage. Colorful birds perch nearby, and a vintage espresso machine occupies one corner. Soft, diffused lighting creates a tranquil atmosphere, perfectly blending the cafe into its rainforest setting. In the style of 3DRNDR", "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: 61710\nPrompt: An old school 3D render of a cozy rainforest cafe on a misty morning. A wooden deck extends into the lush, green canopy, dotted with rustic tables and chairs. Steaming coffee cups and tropical fruit platters rest on some tables, while hanging lanterns and string lights provide ambient illumination. Potted exotic plants decorate the space beneath a partial thatched roof. Mist swirls through surrounding trees, with a distant waterfall visible through the foliage. Colorful birds perch nearby, and a vintage espresso machine occupies one corner. Soft, diffused lighting creates a tranquil atmosphere, perfectly blending the cafe into its rainforest setting. In the style of 3DRNDR\n[!] txt2img mode\nUsing dev model\nfree=8726073053184\nDownloading weights\n2024-09-08T16:04:31Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp3m023wqx/weights url=https://replicate.delivery/yhqm/1rNm3e6AWvXFYKfaxei1079gqwbRdKNnJGrJhSvPFOeGtbrNB/trained_model.tar\n2024-09-08T16:04:33Z | INFO | [ Complete ] dest=/tmp/tmp3m023wqx/weights size=\"172 MB\" total_elapsed=2.047s url=https://replicate.delivery/yhqm/1rNm3e6AWvXFYKfaxei1079gqwbRdKNnJGrJhSvPFOeGtbrNB/trained_model.tar\nDownloaded weights in 2.09s\nLoaded LoRAs in 9.58s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.76it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.24it/s]\n 11%|█ | 3/28 [00:00<00:06, 4.01it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.90it/s]\n 18%|█▊ | 5/28 [00:01<00:05, 3.84it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.81it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.80it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.78it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.77it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.77it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.77it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.76it/s]\n 46%|████▋ | 13/28 [00:03<00:03, 3.77it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.77it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.77it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.76it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.76it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.76it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.76it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.76it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.76it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.76it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.76it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.76it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.76it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.76it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.76it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.76it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.78it/s]", "metrics": { "predict_time": 17.608909324, "total_time": 17.620646 }, "output": [ "https://replicate.delivery/yhqm/OTDc01Ak4arTDBPa6QDe0bH8FFWZB7AluMnsBvF1OUIQ6btJA/out-0.webp" ], "started_at": "2024-09-08T16:04:31.569737Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/8fabc79mrsrm60cht9gtsdthwr", "cancel": "https://api.replicate.com/v1/predictions/8fabc79mrsrm60cht9gtsdthwr/cancel" }, "version": "742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8" }Generated inUsing seed: 61710 Prompt: An old school 3D render of a cozy rainforest cafe on a misty morning. A wooden deck extends into the lush, green canopy, dotted with rustic tables and chairs. Steaming coffee cups and tropical fruit platters rest on some tables, while hanging lanterns and string lights provide ambient illumination. Potted exotic plants decorate the space beneath a partial thatched roof. Mist swirls through surrounding trees, with a distant waterfall visible through the foliage. Colorful birds perch nearby, and a vintage espresso machine occupies one corner. Soft, diffused lighting creates a tranquil atmosphere, perfectly blending the cafe into its rainforest setting. In the style of 3DRNDR [!] txt2img mode Using dev model free=8726073053184 Downloading weights 2024-09-08T16:04:31Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp3m023wqx/weights url=https://replicate.delivery/yhqm/1rNm3e6AWvXFYKfaxei1079gqwbRdKNnJGrJhSvPFOeGtbrNB/trained_model.tar 2024-09-08T16:04:33Z | INFO | [ Complete ] dest=/tmp/tmp3m023wqx/weights size="172 MB" total_elapsed=2.047s url=https://replicate.delivery/yhqm/1rNm3e6AWvXFYKfaxei1079gqwbRdKNnJGrJhSvPFOeGtbrNB/trained_model.tar Downloaded weights in 2.09s Loaded LoRAs in 9.58s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.76it/s] 7%|▋ | 2/28 [00:00<00:06, 4.24it/s] 11%|█ | 3/28 [00:00<00:06, 4.01it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.90it/s] 18%|█▊ | 5/28 [00:01<00:05, 3.84it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.81it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.80it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.78it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.77it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.77it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.77it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.76it/s] 46%|████▋ | 13/28 [00:03<00:03, 3.77it/s] 50%|█████ | 14/28 [00:03<00:03, 3.77it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.77it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.76it/s] 61%|██████ | 17/28 [00:04<00:02, 3.76it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.76it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.76it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.76it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.76it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.76it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.76it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.76it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.76it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.76it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.76it/s] 100%|██████████| 28/28 [00:07<00:00, 3.76it/s] 100%|██████████| 28/28 [00:07<00:00, 3.78it/s]Prediction
paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8ID2qa650s01nrm00cht8stgchjqrStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- an old school 3D render of a flying tiger coming out of its cave in the style of 3DRNDR
- 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": "an old school 3D render of a flying tiger coming out of its cave in the style of 3DRNDR", "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 paulccote/old-school-3d-renders using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8", { input: { model: "dev", prompt: "an old school 3D render of a flying tiger coming out of its cave in the style of 3DRNDR", 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 paulccote/old-school-3d-renders using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8", input={ "model": "dev", "prompt": "an old school 3D render of a flying tiger coming out of its cave in the style of 3DRNDR", "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 paulccote/old-school-3d-renders 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": "paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8", "input": { "model": "dev", "prompt": "an old school 3D render of a flying tiger coming out of its cave in the style of 3DRNDR", "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": "2024-09-08T15:14:38.930185Z", "created_at": "2024-09-08T15:14:11.597000Z", "data_removed": false, "error": null, "id": "2qa650s01nrm00cht8stgchjqr", "input": { "model": "dev", "prompt": "an old school 3D render of a flying tiger coming out of its cave in the style of 3DRNDR", "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: 16528\nPrompt: an old school 3D render of a flying tiger coming out of its cave in the style of 3DRNDR\n[!] txt2img mode\nUsing dev model\nfree=9065692930048\nDownloading weights\n2024-09-08T15:14:19Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpwuun59on/weights url=https://replicate.delivery/yhqm/1rNm3e6AWvXFYKfaxei1079gqwbRdKNnJGrJhSvPFOeGtbrNB/trained_model.tar\n2024-09-08T15:14:22Z | INFO | [ Complete ] dest=/tmp/tmpwuun59on/weights size=\"172 MB\" total_elapsed=2.161s url=https://replicate.delivery/yhqm/1rNm3e6AWvXFYKfaxei1079gqwbRdKNnJGrJhSvPFOeGtbrNB/trained_model.tar\nDownloaded weights in 2.19s\nLoaded LoRAs in 11.18s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.80it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.29it/s]\n 11%|█ | 3/28 [00:00<00:06, 4.05it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.95it/s]\n 18%|█▊ | 5/28 [00:01<00:05, 3.89it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.86it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.84it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.83it/s]\n 32%|███▏ | 9/28 [00:02<00:04, 3.81it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.81it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.80it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.80it/s]\n 46%|████▋ | 13/28 [00:03<00:03, 3.80it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.80it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.80it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.80it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.80it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.79it/s]\n 68%|██████▊ | 19/28 [00:04<00:02, 3.80it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.79it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.80it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.80it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.80it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.79it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.79it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.79it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.79it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.79it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.82it/s]", "metrics": { "predict_time": 19.066650627, "total_time": 27.333185 }, "output": [ "https://replicate.delivery/yhqm/ckciN7cdc5ofI6LpAoaB2EUv4QZf9myUYClrub1sykzeKu1mA/out-0.webp" ], "started_at": "2024-09-08T15:14:19.863534Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/2qa650s01nrm00cht8stgchjqr", "cancel": "https://api.replicate.com/v1/predictions/2qa650s01nrm00cht8stgchjqr/cancel" }, "version": "742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8" }Generated inUsing seed: 16528 Prompt: an old school 3D render of a flying tiger coming out of its cave in the style of 3DRNDR [!] txt2img mode Using dev model free=9065692930048 Downloading weights 2024-09-08T15:14:19Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpwuun59on/weights url=https://replicate.delivery/yhqm/1rNm3e6AWvXFYKfaxei1079gqwbRdKNnJGrJhSvPFOeGtbrNB/trained_model.tar 2024-09-08T15:14:22Z | INFO | [ Complete ] dest=/tmp/tmpwuun59on/weights size="172 MB" total_elapsed=2.161s url=https://replicate.delivery/yhqm/1rNm3e6AWvXFYKfaxei1079gqwbRdKNnJGrJhSvPFOeGtbrNB/trained_model.tar Downloaded weights in 2.19s Loaded LoRAs in 11.18s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.80it/s] 7%|▋ | 2/28 [00:00<00:06, 4.29it/s] 11%|█ | 3/28 [00:00<00:06, 4.05it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.95it/s] 18%|█▊ | 5/28 [00:01<00:05, 3.89it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.86it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.84it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.83it/s] 32%|███▏ | 9/28 [00:02<00:04, 3.81it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.81it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.80it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.80it/s] 46%|████▋ | 13/28 [00:03<00:03, 3.80it/s] 50%|█████ | 14/28 [00:03<00:03, 3.80it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.80it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.80it/s] 61%|██████ | 17/28 [00:04<00:02, 3.80it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.79it/s] 68%|██████▊ | 19/28 [00:04<00:02, 3.80it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.79it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.80it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.80it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.80it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.79it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.79it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.79it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.79it/s] 100%|██████████| 28/28 [00:07<00:00, 3.79it/s] 100%|██████████| 28/28 [00:07<00:00, 3.82it/s]Prediction
paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8IDfmtk4j0kt1rm60cht8yrw1mg30StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- An old school 3D render, low poly, of luoyang china in the style of 3DRNDR
- 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": "An old school 3D render, low poly, of luoyang china in the style of 3DRNDR", "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 paulccote/old-school-3d-renders using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8", { input: { model: "dev", prompt: "An old school 3D render, low poly, of luoyang china in the style of 3DRNDR", 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 paulccote/old-school-3d-renders using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8", input={ "model": "dev", "prompt": "An old school 3D render, low poly, of luoyang china in the style of 3DRNDR", "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 paulccote/old-school-3d-renders 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": "paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8", "input": { "model": "dev", "prompt": "An old school 3D render, low poly, of luoyang china in the style of 3DRNDR", "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": "2024-09-08T15:25:18.820381Z", "created_at": "2024-09-08T15:25:03.824000Z", "data_removed": false, "error": null, "id": "fmtk4j0kt1rm60cht8yrw1mg30", "input": { "model": "dev", "prompt": "An old school 3D render, low poly, of luoyang china in the style of 3DRNDR", "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: 7591\nPrompt: An old school 3D render, low poly, of luoyang china in the style of 3DRNDR\n[!] txt2img mode\nUsing dev model\nLoaded LoRAs in 7.03s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.78it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.26it/s]\n 11%|█ | 3/28 [00:00<00:06, 4.02it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.92it/s]\n 18%|█▊ | 5/28 [00:01<00:05, 3.87it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.83it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.81it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.80it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.79it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.79it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.78it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.78it/s]\n 46%|████▋ | 13/28 [00:03<00:03, 3.78it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.78it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.77it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.77it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.77it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.77it/s]\n 68%|██████▊ | 19/28 [00:04<00:02, 3.77it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.77it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.77it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.77it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.77it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.77it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.77it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.77it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.77it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.78it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.80it/s]", "metrics": { "predict_time": 14.987187515, "total_time": 14.996381 }, "output": [ "https://replicate.delivery/yhqm/FiQKqvd6uPYiLdqxy3e0Ud10Hwb3RQCrtpBTtCMLNjTvnbtJA/out-0.webp" ], "started_at": "2024-09-08T15:25:03.833194Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/fmtk4j0kt1rm60cht8yrw1mg30", "cancel": "https://api.replicate.com/v1/predictions/fmtk4j0kt1rm60cht8yrw1mg30/cancel" }, "version": "742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8" }Generated inUsing seed: 7591 Prompt: An old school 3D render, low poly, of luoyang china in the style of 3DRNDR [!] txt2img mode Using dev model Loaded LoRAs in 7.03s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.78it/s] 7%|▋ | 2/28 [00:00<00:06, 4.26it/s] 11%|█ | 3/28 [00:00<00:06, 4.02it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.92it/s] 18%|█▊ | 5/28 [00:01<00:05, 3.87it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.83it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.81it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.80it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.79it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.79it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.78it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.78it/s] 46%|████▋ | 13/28 [00:03<00:03, 3.78it/s] 50%|█████ | 14/28 [00:03<00:03, 3.78it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.77it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.77it/s] 61%|██████ | 17/28 [00:04<00:02, 3.77it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.77it/s] 68%|██████▊ | 19/28 [00:04<00:02, 3.77it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.77it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.77it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.77it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.77it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.77it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.77it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.77it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.77it/s] 100%|██████████| 28/28 [00:07<00:00, 3.78it/s] 100%|██████████| 28/28 [00:07<00:00, 3.80it/s]Prediction
paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8IDxy5h9x4swhrm40cht91r9kmcs4StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- An old school 3D render of a forest in autumn in the style of 3DRNDR
- 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": "An old school 3D render of a forest in autumn in the style of 3DRNDR", "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 paulccote/old-school-3d-renders using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8", { input: { model: "dev", prompt: "An old school 3D render of a forest in autumn in the style of 3DRNDR", 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 paulccote/old-school-3d-renders using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8", input={ "model": "dev", "prompt": "An old school 3D render of a forest in autumn in the style of 3DRNDR", "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 paulccote/old-school-3d-renders 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": "paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8", "input": { "model": "dev", "prompt": "An old school 3D render of a forest in autumn in the style of 3DRNDR", "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": "2024-09-08T15:32:28.246358Z", "created_at": "2024-09-08T15:32:11.364000Z", "data_removed": false, "error": null, "id": "xy5h9x4swhrm40cht91r9kmcs4", "input": { "model": "dev", "prompt": "An old school 3D render of a forest in autumn in the style of 3DRNDR", "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: 20114\nPrompt: An old school 3D render of a forest in autumn in the style of 3DRNDR\n[!] txt2img mode\nUsing dev model\nfree=8674583343104\nDownloading weights\n2024-09-08T15:32:11Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp12mrk7j4/weights url=https://replicate.delivery/yhqm/1rNm3e6AWvXFYKfaxei1079gqwbRdKNnJGrJhSvPFOeGtbrNB/trained_model.tar\n2024-09-08T15:32:12Z | INFO | [ Complete ] dest=/tmp/tmp12mrk7j4/weights size=\"172 MB\" total_elapsed=1.079s url=https://replicate.delivery/yhqm/1rNm3e6AWvXFYKfaxei1079gqwbRdKNnJGrJhSvPFOeGtbrNB/trained_model.tar\nDownloaded weights in 1.11s\nLoaded LoRAs in 8.88s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.76it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.25it/s]\n 11%|█ | 3/28 [00:00<00:06, 4.01it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.91it/s]\n 18%|█▊ | 5/28 [00:01<00:05, 3.86it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.84it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.81it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.80it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.79it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.79it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.78it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.78it/s]\n 46%|████▋ | 13/28 [00:03<00:03, 3.78it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.78it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.78it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.77it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.77it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.77it/s]\n 68%|██████▊ | 19/28 [00:04<00:02, 3.77it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.77it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.77it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.77it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.77it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.78it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.78it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.78it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.78it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.78it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.80it/s]", "metrics": { "predict_time": 16.872696117, "total_time": 16.882358 }, "output": [ "https://replicate.delivery/yhqm/3H1ZBpGlwaKgIhJGvIXVqemEhRwfTXqm1ZhikmMMnhRMW3aTA/out-0.webp" ], "started_at": "2024-09-08T15:32:11.373662Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/xy5h9x4swhrm40cht91r9kmcs4", "cancel": "https://api.replicate.com/v1/predictions/xy5h9x4swhrm40cht91r9kmcs4/cancel" }, "version": "742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8" }Generated inUsing seed: 20114 Prompt: An old school 3D render of a forest in autumn in the style of 3DRNDR [!] txt2img mode Using dev model free=8674583343104 Downloading weights 2024-09-08T15:32:11Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp12mrk7j4/weights url=https://replicate.delivery/yhqm/1rNm3e6AWvXFYKfaxei1079gqwbRdKNnJGrJhSvPFOeGtbrNB/trained_model.tar 2024-09-08T15:32:12Z | INFO | [ Complete ] dest=/tmp/tmp12mrk7j4/weights size="172 MB" total_elapsed=1.079s url=https://replicate.delivery/yhqm/1rNm3e6AWvXFYKfaxei1079gqwbRdKNnJGrJhSvPFOeGtbrNB/trained_model.tar Downloaded weights in 1.11s Loaded LoRAs in 8.88s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.76it/s] 7%|▋ | 2/28 [00:00<00:06, 4.25it/s] 11%|█ | 3/28 [00:00<00:06, 4.01it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.91it/s] 18%|█▊ | 5/28 [00:01<00:05, 3.86it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.84it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.81it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.80it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.79it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.79it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.78it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.78it/s] 46%|████▋ | 13/28 [00:03<00:03, 3.78it/s] 50%|█████ | 14/28 [00:03<00:03, 3.78it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.78it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.77it/s] 61%|██████ | 17/28 [00:04<00:02, 3.77it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.77it/s] 68%|██████▊ | 19/28 [00:04<00:02, 3.77it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.77it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.77it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.77it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.77it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.78it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.78it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.78it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.78it/s] 100%|██████████| 28/28 [00:07<00:00, 3.78it/s] 100%|██████████| 28/28 [00:07<00:00, 3.80it/s]Prediction
paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8ID73rvb6srs5rm20cht92rkm7hk0StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- An old school 3D render of a monkey at a christmas party in the style of 3DRNDR
- 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": "An old school 3D render of a monkey at a christmas party in the style of 3DRNDR", "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 paulccote/old-school-3d-renders using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8", { input: { model: "dev", prompt: "An old school 3D render of a monkey at a christmas party in the style of 3DRNDR", 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 paulccote/old-school-3d-renders using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8", input={ "model": "dev", "prompt": "An old school 3D render of a monkey at a christmas party in the style of 3DRNDR", "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 paulccote/old-school-3d-renders 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": "paulccote/old-school-3d-renders:742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8", "input": { "model": "dev", "prompt": "An old school 3D render of a monkey at a christmas party in the style of 3DRNDR", "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": "2024-09-08T15:34:13.316230Z", "created_at": "2024-09-08T15:33:57.577000Z", "data_removed": false, "error": null, "id": "73rvb6srs5rm20cht92rkm7hk0", "input": { "model": "dev", "prompt": "An old school 3D render of a monkey at a christmas party in the style of 3DRNDR", "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: 23586\nPrompt: An old school 3D render of a monkey at a christmas party in the style of 3DRNDR\n[!] txt2img mode\nUsing dev model\nLoaded LoRAs in 7.76s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.75it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.24it/s]\n 11%|█ | 3/28 [00:00<00:06, 4.01it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.91it/s]\n 18%|█▊ | 5/28 [00:01<00:05, 3.85it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.82it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.80it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.79it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.78it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.77it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.77it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.76it/s]\n 46%|████▋ | 13/28 [00:03<00:03, 3.76it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.76it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.76it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.76it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.76it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.76it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.76it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.76it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.76it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.76it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.76it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.76it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.76it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.76it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.76it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.76it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.78it/s]", "metrics": { "predict_time": 15.731606035, "total_time": 15.73923 }, "output": [ "https://replicate.delivery/yhqm/BWHfkDqHHWUEDKysOTOkIx9GkAfkT6ikKjpQxd17sFt1X3aTA/out-0.webp" ], "started_at": "2024-09-08T15:33:57.584624Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/73rvb6srs5rm20cht92rkm7hk0", "cancel": "https://api.replicate.com/v1/predictions/73rvb6srs5rm20cht92rkm7hk0/cancel" }, "version": "742c59613d5fb067d57a46f136f383423706c36f496e18dcddf1967f2dd6f2f8" }Generated inUsing seed: 23586 Prompt: An old school 3D render of a monkey at a christmas party in the style of 3DRNDR [!] txt2img mode Using dev model Loaded LoRAs in 7.76s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.75it/s] 7%|▋ | 2/28 [00:00<00:06, 4.24it/s] 11%|█ | 3/28 [00:00<00:06, 4.01it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.91it/s] 18%|█▊ | 5/28 [00:01<00:05, 3.85it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.82it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.80it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.79it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.78it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.77it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.77it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.76it/s] 46%|████▋ | 13/28 [00:03<00:03, 3.76it/s] 50%|█████ | 14/28 [00:03<00:03, 3.76it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.76it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.76it/s] 61%|██████ | 17/28 [00:04<00:02, 3.76it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.76it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.76it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.76it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.76it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.76it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.76it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.76it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.76it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.76it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.76it/s] 100%|██████████| 28/28 [00:07<00:00, 3.76it/s] 100%|██████████| 28/28 [00:07<00:00, 3.78it/s]
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