andreasjansson / flux-allhands
- Public
- 22 runs
-
H100
Prediction
andreasjansson/flux-allhands:33c54769ab5cdf7630a2a7c7a1d1a3a1f9f7c911285b74d8d7a07e62d5f3d3d7ID7yv5excjkhrma0cmc36vdffcz0StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- ALLHNDS video meeting
- go_fast
- lora_scale
- 1.2
- megapixels
- 1
- num_outputs
- 4
- aspect_ratio
- 16:9
- output_format
- png
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "ALLHNDS video meeting", "go_fast": false, "lora_scale": 1.2, "megapixels": "1", "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run andreasjansson/flux-allhands using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "andreasjansson/flux-allhands:33c54769ab5cdf7630a2a7c7a1d1a3a1f9f7c911285b74d8d7a07e62d5f3d3d7", { input: { model: "dev", prompt: "ALLHNDS video meeting", go_fast: false, lora_scale: 1.2, megapixels: "1", num_outputs: 4, aspect_ratio: "16:9", output_format: "png", guidance_scale: 3, output_quality: 80, 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 replicate
Import the client:import replicate
Run andreasjansson/flux-allhands using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "andreasjansson/flux-allhands:33c54769ab5cdf7630a2a7c7a1d1a3a1f9f7c911285b74d8d7a07e62d5f3d3d7", input={ "model": "dev", "prompt": "ALLHNDS video meeting", "go_fast": False, "lora_scale": 1.2, "megapixels": "1", "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3, "output_quality": 80, "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 andreasjansson/flux-allhands 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": "andreasjansson/flux-allhands:33c54769ab5cdf7630a2a7c7a1d1a3a1f9f7c911285b74d8d7a07e62d5f3d3d7", "input": { "model": "dev", "prompt": "ALLHNDS video meeting", "go_fast": false, "lora_scale": 1.2, "megapixels": "1", "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-13T17:55:08.002429Z", "created_at": "2025-01-13T17:54:32.732000Z", "data_removed": false, "error": null, "id": "7yv5excjkhrma0cmc36vdffcz0", "input": { "model": "dev", "prompt": "ALLHNDS video meeting", "go_fast": false, "lora_scale": 1.2, "megapixels": "1", "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2025-01-13 17:54:39.830 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-13 17:54:39.831 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 93%|█████████▎| 282/304 [00:00<00:00, 2817.42it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2707.88it/s]\n2025-01-13 17:54:39.943 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s\nfree=29136000258048\nDownloading weights\n2025-01-13T17:54:39Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpvwjamajb/weights url=https://replicate.delivery/xezq/vkHug8qgN95JLp2rbm5uhmuCTvINFFoF2IOxa17ktBzxEMBF/trained_model.tar\n2025-01-13T17:54:42Z | INFO | [ Complete ] dest=/tmp/tmpvwjamajb/weights size=\"172 MB\" total_elapsed=2.657s url=https://replicate.delivery/xezq/vkHug8qgN95JLp2rbm5uhmuCTvINFFoF2IOxa17ktBzxEMBF/trained_model.tar\nDownloaded weights in 2.68s\n2025-01-13 17:54:42.626 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/252fe4e9521e053e\n2025-01-13 17:54:42.695 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-13 17:54:42.695 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-13 17:54:42.695 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 93%|█████████▎| 283/304 [00:00<00:00, 2820.15it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2713.82it/s]\n2025-01-13 17:54:42.807 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.18s\nUsing seed: 35348\n0it [00:00, ?it/s]\n1it [00:00, 8.40it/s]\n2it [00:00, 5.86it/s]\n3it [00:00, 5.35it/s]\n4it [00:00, 5.13it/s]\n5it [00:00, 4.99it/s]\n6it [00:01, 4.90it/s]\n7it [00:01, 4.86it/s]\n8it [00:01, 4.85it/s]\n9it [00:01, 4.84it/s]\n10it [00:01, 4.82it/s]\n11it [00:02, 4.81it/s]\n12it [00:02, 4.80it/s]\n13it [00:02, 4.80it/s]\n14it [00:02, 4.81it/s]\n15it [00:03, 4.81it/s]\n16it [00:03, 4.80it/s]\n17it [00:03, 4.80it/s]\n18it [00:03, 4.81it/s]\n19it [00:03, 4.80it/s]\n20it [00:04, 4.80it/s]\n21it [00:04, 4.79it/s]\n22it [00:04, 4.79it/s]\n23it [00:04, 4.79it/s]\n24it [00:04, 4.79it/s]\n25it [00:05, 4.79it/s]\n26it [00:05, 4.79it/s]\n27it [00:05, 4.79it/s]\n28it [00:05, 4.79it/s]\n28it [00:05, 4.87it/s]\n0it [00:00, ?it/s]\n1it [00:00, 4.82it/s]\n2it [00:00, 4.79it/s]\n3it [00:00, 4.78it/s]\n4it [00:00, 4.78it/s]\n5it [00:01, 4.80it/s]\n6it [00:01, 4.80it/s]\n7it [00:01, 4.79it/s]\n8it [00:01, 4.79it/s]\n9it [00:01, 4.78it/s]\n10it [00:02, 4.79it/s]\n11it [00:02, 4.78it/s]\n12it [00:02, 4.78it/s]\n13it [00:02, 4.78it/s]\n14it [00:02, 4.78it/s]\n15it [00:03, 4.79it/s]\n16it [00:03, 4.80it/s]\n17it [00:03, 4.80it/s]\n18it [00:03, 4.79it/s]\n19it [00:03, 4.78it/s]\n20it [00:04, 4.77it/s]\n21it [00:04, 4.78it/s]\n22it [00:04, 4.78it/s]\n23it [00:04, 4.77it/s]\n24it [00:05, 4.77it/s]\n25it [00:05, 4.78it/s]\n26it [00:05, 4.80it/s]\n27it [00:05, 4.81it/s]\n28it [00:05, 4.80it/s]\n28it [00:05, 4.79it/s]\n0it [00:00, ?it/s]\n1it [00:00, 4.81it/s]\n2it [00:00, 4.79it/s]\n3it [00:00, 4.79it/s]\n4it [00:00, 4.79it/s]\n5it [00:01, 4.79it/s]\n6it [00:01, 4.78it/s]\n7it [00:01, 4.78it/s]\n8it [00:01, 4.78it/s]\n9it [00:01, 4.78it/s]\n10it [00:02, 4.79it/s]\n11it [00:02, 4.80it/s]\n12it [00:02, 4.80it/s]\n13it [00:02, 4.80it/s]\n14it [00:02, 4.79it/s]\n15it [00:03, 4.79it/s]\n16it [00:03, 4.79it/s]\n17it [00:03, 4.79it/s]\n18it [00:03, 4.79it/s]\n19it [00:03, 4.78it/s]\n20it [00:04, 4.78it/s]\n21it [00:04, 4.78it/s]\n22it [00:04, 4.78it/s]\n23it [00:04, 4.79it/s]\n24it [00:05, 4.79it/s]\n25it [00:05, 4.79it/s]\n26it [00:05, 4.79it/s]\n27it [00:05, 4.79it/s]\n28it [00:05, 4.79it/s]\n28it [00:05, 4.79it/s]\n0it [00:00, ?it/s]\n1it [00:00, 4.83it/s]\n2it [00:00, 4.82it/s]\n3it [00:00, 4.80it/s]\n4it [00:00, 4.79it/s]\n5it [00:01, 4.79it/s]\n6it [00:01, 4.79it/s]\n7it [00:01, 4.79it/s]\n8it [00:01, 4.79it/s]\n9it [00:01, 4.79it/s]\n10it [00:02, 4.79it/s]\n11it [00:02, 4.78it/s]\n12it [00:02, 4.78it/s]\n13it [00:02, 4.78it/s]\n14it [00:02, 4.78it/s]\n15it [00:03, 4.80it/s]\n16it [00:03, 4.80it/s]\n17it [00:03, 4.79it/s]\n18it [00:03, 4.79it/s]\n19it [00:03, 4.78it/s]\n20it [00:04, 4.79it/s]\n21it [00:04, 4.80it/s]\n22it [00:04, 4.79it/s]\n23it [00:04, 4.79it/s]\n24it [00:05, 4.79it/s]\n25it [00:05, 4.79it/s]\n26it [00:05, 4.79it/s]\n27it [00:05, 4.79it/s]\n28it [00:05, 4.80it/s]\n28it [00:05, 4.79it/s]\nTotal safe images: 4 out of 4", "metrics": { "predict_time": 28.17153127, "total_time": 35.270429 }, "output": [ "https://replicate.delivery/xezq/cxet7vagjDXQX6hPvrjSm5RVXDX2cNWMR0moCuBqzpo9KYCKA/out-0.png", "https://replicate.delivery/xezq/a3rWYGqYN7b4JRua2VAe4mLewceAuZdsSbN4qvG15rT3rgJoA/out-1.png", "https://replicate.delivery/xezq/eb6INFTzMRX0TqAk1EFifaj04JW9FOd4S4eoJ5kJZaM2rgJoA/out-2.png", "https://replicate.delivery/xezq/9SLGG8ltShrnA5yVLBixxPZ5BZuj8GfGYPhCfndERKn7VwEUA/out-3.png" ], "started_at": "2025-01-13T17:54:39.830898Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-pc5gohyjijptduxzhxw7zip3shtlqjhxkas2v2yfle3y6qc7kqcq", "get": "https://api.replicate.com/v1/predictions/7yv5excjkhrma0cmc36vdffcz0", "cancel": "https://api.replicate.com/v1/predictions/7yv5excjkhrma0cmc36vdffcz0/cancel" }, "version": "33c54769ab5cdf7630a2a7c7a1d1a3a1f9f7c911285b74d8d7a07e62d5f3d3d7" }
Generated in2025-01-13 17:54:39.830 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-13 17:54:39.831 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 93%|█████████▎| 282/304 [00:00<00:00, 2817.42it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2707.88it/s] 2025-01-13 17:54:39.943 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s free=29136000258048 Downloading weights 2025-01-13T17:54:39Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpvwjamajb/weights url=https://replicate.delivery/xezq/vkHug8qgN95JLp2rbm5uhmuCTvINFFoF2IOxa17ktBzxEMBF/trained_model.tar 2025-01-13T17:54:42Z | INFO | [ Complete ] dest=/tmp/tmpvwjamajb/weights size="172 MB" total_elapsed=2.657s url=https://replicate.delivery/xezq/vkHug8qgN95JLp2rbm5uhmuCTvINFFoF2IOxa17ktBzxEMBF/trained_model.tar Downloaded weights in 2.68s 2025-01-13 17:54:42.626 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/252fe4e9521e053e 2025-01-13 17:54:42.695 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-13 17:54:42.695 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-13 17:54:42.695 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 93%|█████████▎| 283/304 [00:00<00:00, 2820.15it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2713.82it/s] 2025-01-13 17:54:42.807 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.18s Using seed: 35348 0it [00:00, ?it/s] 1it [00:00, 8.40it/s] 2it [00:00, 5.86it/s] 3it [00:00, 5.35it/s] 4it [00:00, 5.13it/s] 5it [00:00, 4.99it/s] 6it [00:01, 4.90it/s] 7it [00:01, 4.86it/s] 8it [00:01, 4.85it/s] 9it [00:01, 4.84it/s] 10it [00:01, 4.82it/s] 11it [00:02, 4.81it/s] 12it [00:02, 4.80it/s] 13it [00:02, 4.80it/s] 14it [00:02, 4.81it/s] 15it [00:03, 4.81it/s] 16it [00:03, 4.80it/s] 17it [00:03, 4.80it/s] 18it [00:03, 4.81it/s] 19it [00:03, 4.80it/s] 20it [00:04, 4.80it/s] 21it [00:04, 4.79it/s] 22it [00:04, 4.79it/s] 23it [00:04, 4.79it/s] 24it [00:04, 4.79it/s] 25it [00:05, 4.79it/s] 26it [00:05, 4.79it/s] 27it [00:05, 4.79it/s] 28it [00:05, 4.79it/s] 28it [00:05, 4.87it/s] 0it [00:00, ?it/s] 1it [00:00, 4.82it/s] 2it [00:00, 4.79it/s] 3it [00:00, 4.78it/s] 4it [00:00, 4.78it/s] 5it [00:01, 4.80it/s] 6it [00:01, 4.80it/s] 7it [00:01, 4.79it/s] 8it [00:01, 4.79it/s] 9it [00:01, 4.78it/s] 10it [00:02, 4.79it/s] 11it [00:02, 4.78it/s] 12it [00:02, 4.78it/s] 13it [00:02, 4.78it/s] 14it [00:02, 4.78it/s] 15it [00:03, 4.79it/s] 16it [00:03, 4.80it/s] 17it [00:03, 4.80it/s] 18it [00:03, 4.79it/s] 19it [00:03, 4.78it/s] 20it [00:04, 4.77it/s] 21it [00:04, 4.78it/s] 22it [00:04, 4.78it/s] 23it [00:04, 4.77it/s] 24it [00:05, 4.77it/s] 25it [00:05, 4.78it/s] 26it [00:05, 4.80it/s] 27it [00:05, 4.81it/s] 28it [00:05, 4.80it/s] 28it [00:05, 4.79it/s] 0it [00:00, ?it/s] 1it [00:00, 4.81it/s] 2it [00:00, 4.79it/s] 3it [00:00, 4.79it/s] 4it [00:00, 4.79it/s] 5it [00:01, 4.79it/s] 6it [00:01, 4.78it/s] 7it [00:01, 4.78it/s] 8it [00:01, 4.78it/s] 9it [00:01, 4.78it/s] 10it [00:02, 4.79it/s] 11it [00:02, 4.80it/s] 12it [00:02, 4.80it/s] 13it [00:02, 4.80it/s] 14it [00:02, 4.79it/s] 15it [00:03, 4.79it/s] 16it [00:03, 4.79it/s] 17it [00:03, 4.79it/s] 18it [00:03, 4.79it/s] 19it [00:03, 4.78it/s] 20it [00:04, 4.78it/s] 21it [00:04, 4.78it/s] 22it [00:04, 4.78it/s] 23it [00:04, 4.79it/s] 24it [00:05, 4.79it/s] 25it [00:05, 4.79it/s] 26it [00:05, 4.79it/s] 27it [00:05, 4.79it/s] 28it [00:05, 4.79it/s] 28it [00:05, 4.79it/s] 0it [00:00, ?it/s] 1it [00:00, 4.83it/s] 2it [00:00, 4.82it/s] 3it [00:00, 4.80it/s] 4it [00:00, 4.79it/s] 5it [00:01, 4.79it/s] 6it [00:01, 4.79it/s] 7it [00:01, 4.79it/s] 8it [00:01, 4.79it/s] 9it [00:01, 4.79it/s] 10it [00:02, 4.79it/s] 11it [00:02, 4.78it/s] 12it [00:02, 4.78it/s] 13it [00:02, 4.78it/s] 14it [00:02, 4.78it/s] 15it [00:03, 4.80it/s] 16it [00:03, 4.80it/s] 17it [00:03, 4.79it/s] 18it [00:03, 4.79it/s] 19it [00:03, 4.78it/s] 20it [00:04, 4.79it/s] 21it [00:04, 4.80it/s] 22it [00:04, 4.79it/s] 23it [00:04, 4.79it/s] 24it [00:05, 4.79it/s] 25it [00:05, 4.79it/s] 26it [00:05, 4.79it/s] 27it [00:05, 4.79it/s] 28it [00:05, 4.80it/s] 28it [00:05, 4.79it/s] Total safe images: 4 out of 4
Prediction
andreasjansson/flux-allhands:33c54769ab5cdf7630a2a7c7a1d1a3a1f9f7c911285b74d8d7a07e62d5f3d3d7ID7g0bpspfx9rme0cmc38syp03xmStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- ALLHNDS video meeting
- go_fast
- lora_scale
- 1.2
- megapixels
- 1
- num_outputs
- 4
- aspect_ratio
- 16:9
- output_format
- png
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "ALLHNDS video meeting", "go_fast": false, "lora_scale": 1.2, "megapixels": "1", "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run andreasjansson/flux-allhands using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "andreasjansson/flux-allhands:33c54769ab5cdf7630a2a7c7a1d1a3a1f9f7c911285b74d8d7a07e62d5f3d3d7", { input: { model: "dev", prompt: "ALLHNDS video meeting", go_fast: false, lora_scale: 1.2, megapixels: "1", num_outputs: 4, aspect_ratio: "16:9", output_format: "png", guidance_scale: 3, output_quality: 80, 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 replicate
Import the client:import replicate
Run andreasjansson/flux-allhands using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "andreasjansson/flux-allhands:33c54769ab5cdf7630a2a7c7a1d1a3a1f9f7c911285b74d8d7a07e62d5f3d3d7", input={ "model": "dev", "prompt": "ALLHNDS video meeting", "go_fast": False, "lora_scale": 1.2, "megapixels": "1", "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3, "output_quality": 80, "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 andreasjansson/flux-allhands 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": "andreasjansson/flux-allhands:33c54769ab5cdf7630a2a7c7a1d1a3a1f9f7c911285b74d8d7a07e62d5f3d3d7", "input": { "model": "dev", "prompt": "ALLHNDS video meeting", "go_fast": false, "lora_scale": 1.2, "megapixels": "1", "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-13T17:59:38.930865Z", "created_at": "2025-01-13T17:59:10.570000Z", "data_removed": false, "error": null, "id": "7g0bpspfx9rme0cmc38syp03xm", "input": { "model": "dev", "prompt": "ALLHNDS video meeting", "go_fast": false, "lora_scale": 1.2, "megapixels": "1", "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2025-01-13 17:59:13.720 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-13 17:59:13.720 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 93%|█████████▎| 284/304 [00:00<00:00, 2836.20it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2717.50it/s]\n2025-01-13 17:59:13.833 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s\n2025-01-13 17:59:13.834 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/252fe4e9521e053e\n2025-01-13 17:59:13.950 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-13 17:59:13.950 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-13 17:59:13.950 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 94%|█████████▍| 285/304 [00:00<00:00, 2835.68it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2722.18it/s]\n2025-01-13 17:59:14.062 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s\nUsing seed: 19231\n0it [00:00, ?it/s]\n1it [00:00, 8.45it/s]\n2it [00:00, 5.91it/s]\n3it [00:00, 5.39it/s]\n4it [00:00, 5.18it/s]\n5it [00:00, 5.05it/s]\n6it [00:01, 4.97it/s]\n7it [00:01, 4.92it/s]\n8it [00:01, 4.90it/s]\n9it [00:01, 4.89it/s]\n10it [00:01, 4.88it/s]\n11it [00:02, 4.87it/s]\n12it [00:02, 4.86it/s]\n13it [00:02, 4.86it/s]\n14it [00:02, 4.86it/s]\n15it [00:03, 4.87it/s]\n16it [00:03, 4.87it/s]\n17it [00:03, 4.86it/s]\n18it [00:03, 4.86it/s]\n19it [00:03, 4.86it/s]\n20it [00:04, 4.86it/s]\n21it [00:04, 4.86it/s]\n22it [00:04, 4.85it/s]\n23it [00:04, 4.85it/s]\n24it [00:04, 4.85it/s]\n25it [00:05, 4.85it/s]\n26it [00:05, 4.85it/s]\n27it [00:05, 4.85it/s]\n28it [00:05, 4.86it/s]\n28it [00:05, 4.93it/s]\n0it [00:00, ?it/s]\n1it [00:00, 4.93it/s]\n2it [00:00, 4.89it/s]\n3it [00:00, 4.87it/s]\n4it [00:00, 4.86it/s]\n5it [00:01, 4.85it/s]\n6it [00:01, 4.86it/s]\n7it [00:01, 4.87it/s]\n8it [00:01, 4.86it/s]\n9it [00:01, 4.87it/s]\n10it [00:02, 4.87it/s]\n11it [00:02, 4.86it/s]\n12it [00:02, 4.87it/s]\n13it [00:02, 4.86it/s]\n14it [00:02, 4.87it/s]\n15it [00:03, 4.87it/s]\n16it [00:03, 4.87it/s]\n17it [00:03, 4.87it/s]\n18it [00:03, 4.87it/s]\n19it [00:03, 4.87it/s]\n20it [00:04, 4.87it/s]\n21it [00:04, 4.88it/s]\n22it [00:04, 4.88it/s]\n23it [00:04, 4.87it/s]\n24it [00:04, 4.87it/s]\n25it [00:05, 4.87it/s]\n26it [00:05, 4.87it/s]\n27it [00:05, 4.87it/s]\n28it [00:05, 4.87it/s]\n28it [00:05, 4.87it/s]\n0it [00:00, ?it/s]\n1it [00:00, 4.92it/s]\n2it [00:00, 4.88it/s]\n3it [00:00, 4.87it/s]\n4it [00:00, 4.86it/s]\n5it [00:01, 4.87it/s]\n6it [00:01, 4.86it/s]\n7it [00:01, 4.86it/s]\n8it [00:01, 4.87it/s]\n9it [00:01, 4.86it/s]\n10it [00:02, 4.86it/s]\n11it [00:02, 4.86it/s]\n12it [00:02, 4.86it/s]\n13it [00:02, 4.86it/s]\n14it [00:02, 4.86it/s]\n15it [00:03, 4.86it/s]\n16it [00:03, 4.86it/s]\n17it [00:03, 4.86it/s]\n18it [00:03, 4.86it/s]\n19it [00:03, 4.86it/s]\n20it [00:04, 4.86it/s]\n21it [00:04, 4.86it/s]\n22it [00:04, 4.87it/s]\n23it [00:04, 4.87it/s]\n24it [00:04, 4.87it/s]\n25it [00:05, 4.87it/s]\n26it [00:05, 4.87it/s]\n27it [00:05, 4.87it/s]\n28it [00:05, 4.87it/s]\n28it [00:05, 4.86it/s]\n0it [00:00, ?it/s]\n1it [00:00, 4.92it/s]\n2it [00:00, 4.89it/s]\n3it [00:00, 4.88it/s]\n4it [00:00, 4.87it/s]\n5it [00:01, 4.87it/s]\n6it [00:01, 4.87it/s]\n7it [00:01, 4.87it/s]\n8it [00:01, 4.86it/s]\n9it [00:01, 4.86it/s]\n10it [00:02, 4.86it/s]\n11it [00:02, 4.86it/s]\n12it [00:02, 4.86it/s]\n13it [00:02, 4.87it/s]\n14it [00:02, 4.87it/s]\n15it [00:03, 4.87it/s]\n16it [00:03, 4.87it/s]\n17it [00:03, 4.86it/s]\n18it [00:03, 4.86it/s]\n19it [00:03, 4.86it/s]\n20it [00:04, 4.86it/s]\n21it [00:04, 4.86it/s]\n22it [00:04, 4.86it/s]\n23it [00:04, 4.86it/s]\n24it [00:04, 4.87it/s]\n25it [00:05, 4.87it/s]\n26it [00:05, 4.87it/s]\n27it [00:05, 4.86it/s]\n28it [00:05, 4.86it/s]\n28it [00:05, 4.87it/s]\nTotal safe images: 4 out of 4", "metrics": { "predict_time": 25.209510051, "total_time": 28.360865 }, "output": [ "https://replicate.delivery/xezq/Pfvqpi3fVMucXEY7SeMQXpQVgSbGcAth6RPy239F8SlU0gJoA/out-0.png", "https://replicate.delivery/xezq/vLR5dSGQDIarJtAMyq0IZ49KGeoKBWnQpEvxiJyeeFFU0gJoA/out-1.png", "https://replicate.delivery/xezq/DxkDXmWCnN4kJtthO2fDY6afm4onmyRBYaftOt4V9zhV0gJoA/out-2.png", "https://replicate.delivery/xezq/z3U5DpeYMwQCAKYu6gVSpgpfjJStxBVPNZ0hpDgcfF8U0gJoA/out-3.png" ], "started_at": "2025-01-13T17:59:13.721355Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-okhkfuyvkqrgqbqrlkwktjw3bioibxtrvso7w3bcsnyzphsznk7a", "get": "https://api.replicate.com/v1/predictions/7g0bpspfx9rme0cmc38syp03xm", "cancel": "https://api.replicate.com/v1/predictions/7g0bpspfx9rme0cmc38syp03xm/cancel" }, "version": "33c54769ab5cdf7630a2a7c7a1d1a3a1f9f7c911285b74d8d7a07e62d5f3d3d7" }
Generated in2025-01-13 17:59:13.720 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-13 17:59:13.720 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 93%|█████████▎| 284/304 [00:00<00:00, 2836.20it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2717.50it/s] 2025-01-13 17:59:13.833 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s 2025-01-13 17:59:13.834 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/252fe4e9521e053e 2025-01-13 17:59:13.950 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-13 17:59:13.950 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-13 17:59:13.950 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 94%|█████████▍| 285/304 [00:00<00:00, 2835.68it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2722.18it/s] 2025-01-13 17:59:14.062 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s Using seed: 19231 0it [00:00, ?it/s] 1it [00:00, 8.45it/s] 2it [00:00, 5.91it/s] 3it [00:00, 5.39it/s] 4it [00:00, 5.18it/s] 5it [00:00, 5.05it/s] 6it [00:01, 4.97it/s] 7it [00:01, 4.92it/s] 8it [00:01, 4.90it/s] 9it [00:01, 4.89it/s] 10it [00:01, 4.88it/s] 11it [00:02, 4.87it/s] 12it [00:02, 4.86it/s] 13it [00:02, 4.86it/s] 14it [00:02, 4.86it/s] 15it [00:03, 4.87it/s] 16it [00:03, 4.87it/s] 17it [00:03, 4.86it/s] 18it [00:03, 4.86it/s] 19it [00:03, 4.86it/s] 20it [00:04, 4.86it/s] 21it [00:04, 4.86it/s] 22it [00:04, 4.85it/s] 23it [00:04, 4.85it/s] 24it [00:04, 4.85it/s] 25it [00:05, 4.85it/s] 26it [00:05, 4.85it/s] 27it [00:05, 4.85it/s] 28it [00:05, 4.86it/s] 28it [00:05, 4.93it/s] 0it [00:00, ?it/s] 1it [00:00, 4.93it/s] 2it [00:00, 4.89it/s] 3it [00:00, 4.87it/s] 4it [00:00, 4.86it/s] 5it [00:01, 4.85it/s] 6it [00:01, 4.86it/s] 7it [00:01, 4.87it/s] 8it [00:01, 4.86it/s] 9it [00:01, 4.87it/s] 10it [00:02, 4.87it/s] 11it [00:02, 4.86it/s] 12it [00:02, 4.87it/s] 13it [00:02, 4.86it/s] 14it [00:02, 4.87it/s] 15it [00:03, 4.87it/s] 16it [00:03, 4.87it/s] 17it [00:03, 4.87it/s] 18it [00:03, 4.87it/s] 19it [00:03, 4.87it/s] 20it [00:04, 4.87it/s] 21it [00:04, 4.88it/s] 22it [00:04, 4.88it/s] 23it [00:04, 4.87it/s] 24it [00:04, 4.87it/s] 25it [00:05, 4.87it/s] 26it [00:05, 4.87it/s] 27it [00:05, 4.87it/s] 28it [00:05, 4.87it/s] 28it [00:05, 4.87it/s] 0it [00:00, ?it/s] 1it [00:00, 4.92it/s] 2it [00:00, 4.88it/s] 3it [00:00, 4.87it/s] 4it [00:00, 4.86it/s] 5it [00:01, 4.87it/s] 6it [00:01, 4.86it/s] 7it [00:01, 4.86it/s] 8it [00:01, 4.87it/s] 9it [00:01, 4.86it/s] 10it [00:02, 4.86it/s] 11it [00:02, 4.86it/s] 12it [00:02, 4.86it/s] 13it [00:02, 4.86it/s] 14it [00:02, 4.86it/s] 15it [00:03, 4.86it/s] 16it [00:03, 4.86it/s] 17it [00:03, 4.86it/s] 18it [00:03, 4.86it/s] 19it [00:03, 4.86it/s] 20it [00:04, 4.86it/s] 21it [00:04, 4.86it/s] 22it [00:04, 4.87it/s] 23it [00:04, 4.87it/s] 24it [00:04, 4.87it/s] 25it [00:05, 4.87it/s] 26it [00:05, 4.87it/s] 27it [00:05, 4.87it/s] 28it [00:05, 4.87it/s] 28it [00:05, 4.86it/s] 0it [00:00, ?it/s] 1it [00:00, 4.92it/s] 2it [00:00, 4.89it/s] 3it [00:00, 4.88it/s] 4it [00:00, 4.87it/s] 5it [00:01, 4.87it/s] 6it [00:01, 4.87it/s] 7it [00:01, 4.87it/s] 8it [00:01, 4.86it/s] 9it [00:01, 4.86it/s] 10it [00:02, 4.86it/s] 11it [00:02, 4.86it/s] 12it [00:02, 4.86it/s] 13it [00:02, 4.87it/s] 14it [00:02, 4.87it/s] 15it [00:03, 4.87it/s] 16it [00:03, 4.87it/s] 17it [00:03, 4.86it/s] 18it [00:03, 4.86it/s] 19it [00:03, 4.86it/s] 20it [00:04, 4.86it/s] 21it [00:04, 4.86it/s] 22it [00:04, 4.86it/s] 23it [00:04, 4.86it/s] 24it [00:04, 4.87it/s] 25it [00:05, 4.87it/s] 26it [00:05, 4.87it/s] 27it [00:05, 4.86it/s] 28it [00:05, 4.86it/s] 28it [00:05, 4.87it/s] Total safe images: 4 out of 4
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