jbilcke / flux-satellite
- Public
- 26 runs
-
H100
Prediction
jbilcke/flux-satellite:c47bcf2556da63e15da1e382b15d200ca39bd55e9e37a3315de57367ac049532ID53pxgptqa1rmc0cmm9zbj04r7mStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- satellite view of a small city, american suburb, in the style of TOK
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 50
{ "model": "dev", "prompt": "satellite view of a small city, american suburb, in the style of TOK", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 }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 jbilcke/flux-satellite using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "jbilcke/flux-satellite:c47bcf2556da63e15da1e382b15d200ca39bd55e9e37a3315de57367ac049532", { input: { model: "dev", prompt: "satellite view of a small city, american suburb, in the style of TOK", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 50 } } ); // 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 jbilcke/flux-satellite using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "jbilcke/flux-satellite:c47bcf2556da63e15da1e382b15d200ca39bd55e9e37a3315de57367ac049532", input={ "model": "dev", "prompt": "satellite view of a small city, american suburb, in the style of TOK", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run jbilcke/flux-satellite 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": "jbilcke/flux-satellite:c47bcf2556da63e15da1e382b15d200ca39bd55e9e37a3315de57367ac049532", "input": { "model": "dev", "prompt": "satellite view of a small city, american suburb, in the style of TOK", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-26T12:03:10.642394Z", "created_at": "2025-01-26T12:02:56.464000Z", "data_removed": false, "error": null, "id": "53pxgptqa1rmc0cmm9zbj04r7m", "input": { "model": "dev", "prompt": "satellite view of a small city, american suburb, in the style of TOK", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 }, "logs": "2025-01-26 12:02:56.536 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-26 12:02:56.536 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 91%|█████████ | 276/304 [00:00<00:00, 2755.90it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2619.89it/s]\n2025-01-26 12:02:56.653 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s\nfree=28683639476224\nDownloading weights\n2025-01-26T12:02:56Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpytyyhf92/weights url=https://replicate.delivery/xezq/QK4xz8puPDYrHBVLKkQbXdl4FUuuZ7Z087J1CjMmgpVHTPCF/trained_model.tar\n2025-01-26T12:02:59Z | INFO | [ Complete ] dest=/tmp/tmpytyyhf92/weights size=\"172 MB\" total_elapsed=3.048s url=https://replicate.delivery/xezq/QK4xz8puPDYrHBVLKkQbXdl4FUuuZ7Z087J1CjMmgpVHTPCF/trained_model.tar\nDownloaded weights in 3.07s\n2025-01-26 12:02:59.730 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/ddbb496db14417cf\n2025-01-26 12:02:59.801 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-26 12:02:59.801 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-26 12:02:59.801 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 91%|█████████ | 276/304 [00:00<00:00, 2756.62it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2620.69it/s]\n2025-01-26 12:02:59.918 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s\nUsing seed: 59211\n0it [00:00, ?it/s]\n1it [00:00, 8.33it/s]\n2it [00:00, 5.85it/s]\n3it [00:00, 5.34it/s]\n4it [00:00, 5.13it/s]\n5it [00:00, 5.02it/s]\n6it [00:01, 4.95it/s]\n7it [00:01, 4.91it/s]\n8it [00:01, 4.89it/s]\n9it [00:01, 4.87it/s]\n10it [00:01, 4.86it/s]\n11it [00:02, 4.85it/s]\n12it [00:02, 4.83it/s]\n13it [00:02, 4.83it/s]\n14it [00:02, 4.83it/s]\n15it [00:03, 4.83it/s]\n16it [00:03, 4.83it/s]\n17it [00:03, 4.83it/s]\n18it [00:03, 4.83it/s]\n19it [00:03, 4.82it/s]\n20it [00:04, 4.82it/s]\n21it [00:04, 4.82it/s]\n22it [00:04, 4.82it/s]\n23it [00:04, 4.82it/s]\n24it [00:04, 4.82it/s]\n25it [00:05, 4.82it/s]\n26it [00:05, 4.82it/s]\n27it [00:05, 4.82it/s]\n28it [00:05, 4.82it/s]\n29it [00:05, 4.82it/s]\n30it [00:06, 4.82it/s]\n31it [00:06, 4.81it/s]\n32it [00:06, 4.81it/s]\n33it [00:06, 4.81it/s]\n34it [00:06, 4.81it/s]\n35it [00:07, 4.81it/s]\n36it [00:07, 4.81it/s]\n37it [00:07, 4.82it/s]\n38it [00:07, 4.82it/s]\n39it [00:08, 4.81it/s]\n40it [00:08, 4.81it/s]\n41it [00:08, 4.82it/s]\n42it [00:08, 4.82it/s]\n43it [00:08, 4.81it/s]\n44it [00:09, 4.81it/s]\n45it [00:09, 4.81it/s]\n46it [00:09, 4.80it/s]\n47it [00:09, 4.81it/s]\n48it [00:09, 4.81it/s]\n49it [00:10, 4.81it/s]\n50it [00:10, 4.80it/s]\n50it [00:10, 4.86it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 14.105075315, "total_time": 14.178394 }, "output": [ "https://replicate.delivery/xezq/0GuYgrqVaWrLNhk60pqIGggiPNopRX5RrQ26LxjzvqofseIUA/out-0.webp" ], "started_at": "2025-01-26T12:02:56.537318Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bsvm-cqrkgvv5kte6q6ac7gjvjsflyejnivicbrvg7r37dixhlppjfd2q", "get": "https://api.replicate.com/v1/predictions/53pxgptqa1rmc0cmm9zbj04r7m", "cancel": "https://api.replicate.com/v1/predictions/53pxgptqa1rmc0cmm9zbj04r7m/cancel" }, "version": "c47bcf2556da63e15da1e382b15d200ca39bd55e9e37a3315de57367ac049532" }Generated in2025-01-26 12:02:56.536 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-26 12:02:56.536 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 91%|█████████ | 276/304 [00:00<00:00, 2755.90it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2619.89it/s] 2025-01-26 12:02:56.653 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s free=28683639476224 Downloading weights 2025-01-26T12:02:56Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpytyyhf92/weights url=https://replicate.delivery/xezq/QK4xz8puPDYrHBVLKkQbXdl4FUuuZ7Z087J1CjMmgpVHTPCF/trained_model.tar 2025-01-26T12:02:59Z | INFO | [ Complete ] dest=/tmp/tmpytyyhf92/weights size="172 MB" total_elapsed=3.048s url=https://replicate.delivery/xezq/QK4xz8puPDYrHBVLKkQbXdl4FUuuZ7Z087J1CjMmgpVHTPCF/trained_model.tar Downloaded weights in 3.07s 2025-01-26 12:02:59.730 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/ddbb496db14417cf 2025-01-26 12:02:59.801 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-26 12:02:59.801 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-26 12:02:59.801 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 91%|█████████ | 276/304 [00:00<00:00, 2756.62it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2620.69it/s] 2025-01-26 12:02:59.918 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s Using seed: 59211 0it [00:00, ?it/s] 1it [00:00, 8.33it/s] 2it [00:00, 5.85it/s] 3it [00:00, 5.34it/s] 4it [00:00, 5.13it/s] 5it [00:00, 5.02it/s] 6it [00:01, 4.95it/s] 7it [00:01, 4.91it/s] 8it [00:01, 4.89it/s] 9it [00:01, 4.87it/s] 10it [00:01, 4.86it/s] 11it [00:02, 4.85it/s] 12it [00:02, 4.83it/s] 13it [00:02, 4.83it/s] 14it [00:02, 4.83it/s] 15it [00:03, 4.83it/s] 16it [00:03, 4.83it/s] 17it [00:03, 4.83it/s] 18it [00:03, 4.83it/s] 19it [00:03, 4.82it/s] 20it [00:04, 4.82it/s] 21it [00:04, 4.82it/s] 22it [00:04, 4.82it/s] 23it [00:04, 4.82it/s] 24it [00:04, 4.82it/s] 25it [00:05, 4.82it/s] 26it [00:05, 4.82it/s] 27it [00:05, 4.82it/s] 28it [00:05, 4.82it/s] 29it [00:05, 4.82it/s] 30it [00:06, 4.82it/s] 31it [00:06, 4.81it/s] 32it [00:06, 4.81it/s] 33it [00:06, 4.81it/s] 34it [00:06, 4.81it/s] 35it [00:07, 4.81it/s] 36it [00:07, 4.81it/s] 37it [00:07, 4.82it/s] 38it [00:07, 4.82it/s] 39it [00:08, 4.81it/s] 40it [00:08, 4.81it/s] 41it [00:08, 4.82it/s] 42it [00:08, 4.82it/s] 43it [00:08, 4.81it/s] 44it [00:09, 4.81it/s] 45it [00:09, 4.81it/s] 46it [00:09, 4.80it/s] 47it [00:09, 4.81it/s] 48it [00:09, 4.81it/s] 49it [00:10, 4.81it/s] 50it [00:10, 4.80it/s] 50it [00:10, 4.86it/s] Total safe images: 1 out of 1Prediction
jbilcke/flux-satellite:c47bcf2556da63e15da1e382b15d200ca39bd55e9e37a3315de57367ac049532ID2q813hb935rm80cmma0b8de4qwStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- satellite view of a small traditional french europe city, in the style of TOK
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 50
{ "model": "dev", "prompt": "satellite view of a small traditional french europe city, in the style of TOK", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 }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 jbilcke/flux-satellite using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "jbilcke/flux-satellite:c47bcf2556da63e15da1e382b15d200ca39bd55e9e37a3315de57367ac049532", { input: { model: "dev", prompt: "satellite view of a small traditional french europe city, in the style of TOK", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 50 } } ); // 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 jbilcke/flux-satellite using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "jbilcke/flux-satellite:c47bcf2556da63e15da1e382b15d200ca39bd55e9e37a3315de57367ac049532", input={ "model": "dev", "prompt": "satellite view of a small traditional french europe city, in the style of TOK", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run jbilcke/flux-satellite 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": "jbilcke/flux-satellite:c47bcf2556da63e15da1e382b15d200ca39bd55e9e37a3315de57367ac049532", "input": { "model": "dev", "prompt": "satellite view of a small traditional french europe city, in the style of TOK", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-26T12:05:25.377201Z", "created_at": "2025-01-26T12:05:12.089000Z", "data_removed": false, "error": null, "id": "2q813hb935rm80cmma0b8de4qw", "input": { "model": "dev", "prompt": "satellite view of a small traditional french europe city, in the style of TOK", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 }, "logs": "2025-01-26 12:05:12.104 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-26 12:05:12.105 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 96%|█████████▌| 291/304 [00:00<00:00, 2903.10it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2820.02it/s]\n2025-01-26 12:05:12.213 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-26 12:05:12.213 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 53%|█████▎ | 161/304 [00:00<00:00, 1609.74it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 1733.53it/s]\n2025-01-26 12:05:12.389 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.28s\nfree=28895027511296\nDownloading weights\n2025-01-26T12:05:12Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmptjc19z7u/weights url=https://replicate.delivery/xezq/QK4xz8puPDYrHBVLKkQbXdl4FUuuZ7Z087J1CjMmgpVHTPCF/trained_model.tar\n2025-01-26T12:05:14Z | INFO | [ Complete ] dest=/tmp/tmptjc19z7u/weights size=\"172 MB\" total_elapsed=1.936s url=https://replicate.delivery/xezq/QK4xz8puPDYrHBVLKkQbXdl4FUuuZ7Z087J1CjMmgpVHTPCF/trained_model.tar\nDownloaded weights in 1.96s\n2025-01-26 12:05:14.355 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/ddbb496db14417cf\n2025-01-26 12:05:14.428 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-26 12:05:14.428 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-26 12:05:14.428 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 92%|█████████▏| 279/304 [00:00<00:00, 2784.40it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2663.43it/s]\n2025-01-26 12:05:14.543 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s\nUsing seed: 273\n0it [00:00, ?it/s]\n1it [00:00, 8.32it/s]\n2it [00:00, 5.80it/s]\n3it [00:00, 5.30it/s]\n4it [00:00, 5.09it/s]\n5it [00:00, 4.95it/s]\n6it [00:01, 4.87it/s]\n7it [00:01, 4.85it/s]\n8it [00:01, 4.83it/s]\n9it [00:01, 4.82it/s]\n10it [00:02, 4.79it/s]\n11it [00:02, 4.77it/s]\n12it [00:02, 4.77it/s]\n13it [00:02, 4.78it/s]\n14it [00:02, 4.77it/s]\n15it [00:03, 4.76it/s]\n16it [00:03, 4.75it/s]\n17it [00:03, 4.76it/s]\n18it [00:03, 4.76it/s]\n19it [00:03, 4.76it/s]\n20it [00:04, 4.76it/s]\n21it [00:04, 4.76it/s]\n22it [00:04, 4.77it/s]\n23it [00:04, 4.78it/s]\n24it [00:04, 4.78it/s]\n25it [00:05, 4.77it/s]\n26it [00:05, 4.77it/s]\n27it [00:05, 4.76it/s]\n28it [00:05, 4.77it/s]\n29it [00:05, 4.77it/s]\n30it [00:06, 4.77it/s]\n31it [00:06, 4.76it/s]\n32it [00:06, 4.76it/s]\n33it [00:06, 4.76it/s]\n34it [00:07, 4.76it/s]\n35it [00:07, 4.76it/s]\n36it [00:07, 4.76it/s]\n37it [00:07, 4.76it/s]\n38it [00:07, 4.76it/s]\n39it [00:08, 4.77it/s]\n40it [00:08, 4.76it/s]\n41it [00:08, 4.76it/s]\n42it [00:08, 4.75it/s]\n43it [00:08, 4.76it/s]\n44it [00:09, 4.76it/s]\n45it [00:09, 4.76it/s]\n46it [00:09, 4.75it/s]\n47it [00:09, 4.75it/s]\n48it [00:09, 4.75it/s]\n49it [00:10, 4.76it/s]\n50it [00:10, 4.76it/s]\n50it [00:10, 4.80it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 13.271529591, "total_time": 13.288201 }, "output": [ "https://replicate.delivery/xezq/4vUad1VteayORKYyl7UlSciL3FXJGLWvhf79m75Y1jHFc9IUA/out-0.webp" ], "started_at": "2025-01-26T12:05:12.105671Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bsvm-p6ytp3pbjanhao42ascjnwgbymof4frd46qkyag54yutk635pcpq", "get": "https://api.replicate.com/v1/predictions/2q813hb935rm80cmma0b8de4qw", "cancel": "https://api.replicate.com/v1/predictions/2q813hb935rm80cmma0b8de4qw/cancel" }, "version": "c47bcf2556da63e15da1e382b15d200ca39bd55e9e37a3315de57367ac049532" }Generated in2025-01-26 12:05:12.104 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-26 12:05:12.105 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 96%|█████████▌| 291/304 [00:00<00:00, 2903.10it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2820.02it/s] 2025-01-26 12:05:12.213 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-26 12:05:12.213 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 53%|█████▎ | 161/304 [00:00<00:00, 1609.74it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 1733.53it/s] 2025-01-26 12:05:12.389 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.28s free=28895027511296 Downloading weights 2025-01-26T12:05:12Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmptjc19z7u/weights url=https://replicate.delivery/xezq/QK4xz8puPDYrHBVLKkQbXdl4FUuuZ7Z087J1CjMmgpVHTPCF/trained_model.tar 2025-01-26T12:05:14Z | INFO | [ Complete ] dest=/tmp/tmptjc19z7u/weights size="172 MB" total_elapsed=1.936s url=https://replicate.delivery/xezq/QK4xz8puPDYrHBVLKkQbXdl4FUuuZ7Z087J1CjMmgpVHTPCF/trained_model.tar Downloaded weights in 1.96s 2025-01-26 12:05:14.355 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/ddbb496db14417cf 2025-01-26 12:05:14.428 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-26 12:05:14.428 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-26 12:05:14.428 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 92%|█████████▏| 279/304 [00:00<00:00, 2784.40it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2663.43it/s] 2025-01-26 12:05:14.543 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s Using seed: 273 0it [00:00, ?it/s] 1it [00:00, 8.32it/s] 2it [00:00, 5.80it/s] 3it [00:00, 5.30it/s] 4it [00:00, 5.09it/s] 5it [00:00, 4.95it/s] 6it [00:01, 4.87it/s] 7it [00:01, 4.85it/s] 8it [00:01, 4.83it/s] 9it [00:01, 4.82it/s] 10it [00:02, 4.79it/s] 11it [00:02, 4.77it/s] 12it [00:02, 4.77it/s] 13it [00:02, 4.78it/s] 14it [00:02, 4.77it/s] 15it [00:03, 4.76it/s] 16it [00:03, 4.75it/s] 17it [00:03, 4.76it/s] 18it [00:03, 4.76it/s] 19it [00:03, 4.76it/s] 20it [00:04, 4.76it/s] 21it [00:04, 4.76it/s] 22it [00:04, 4.77it/s] 23it [00:04, 4.78it/s] 24it [00:04, 4.78it/s] 25it [00:05, 4.77it/s] 26it [00:05, 4.77it/s] 27it [00:05, 4.76it/s] 28it [00:05, 4.77it/s] 29it [00:05, 4.77it/s] 30it [00:06, 4.77it/s] 31it [00:06, 4.76it/s] 32it [00:06, 4.76it/s] 33it [00:06, 4.76it/s] 34it [00:07, 4.76it/s] 35it [00:07, 4.76it/s] 36it [00:07, 4.76it/s] 37it [00:07, 4.76it/s] 38it [00:07, 4.76it/s] 39it [00:08, 4.77it/s] 40it [00:08, 4.76it/s] 41it [00:08, 4.76it/s] 42it [00:08, 4.75it/s] 43it [00:08, 4.76it/s] 44it [00:09, 4.76it/s] 45it [00:09, 4.76it/s] 46it [00:09, 4.75it/s] 47it [00:09, 4.75it/s] 48it [00:09, 4.75it/s] 49it [00:10, 4.76it/s] 50it [00:10, 4.76it/s] 50it [00:10, 4.80it/s] Total safe images: 1 out of 1
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