fofr
/
flux-handwriting
A flux lora fine-tuned to produce handwritten text
- Public
- 2.4K runs
-
H100
- Weights
Prediction
fofr/flux-handwriting:786bc82c11569935506ad1d9ae1b712c0a274cc4b75c23d2d9bd42e232540f1eID7qc3px66q9rma0ckrm5ahx0bqwStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- HWRIT handwriting saying "Hello, this is a handrwriting lora", messy style, blue ink on paper
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- jpg
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "HWRIT handwriting saying \"Hello, this is a handrwriting lora\", messy style, blue ink on paper", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "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 replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/flux-handwriting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-handwriting:786bc82c11569935506ad1d9ae1b712c0a274cc4b75c23d2d9bd42e232540f1e", { input: { model: "dev", prompt: "HWRIT handwriting saying \"Hello, this is a handrwriting lora\", messy style, blue ink on paper", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "jpg", 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 replicateImport the client:import replicateRun fofr/flux-handwriting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-handwriting:786bc82c11569935506ad1d9ae1b712c0a274cc4b75c23d2d9bd42e232540f1e", input={ "model": "dev", "prompt": "HWRIT handwriting saying \"Hello, this is a handrwriting lora\", messy style, blue ink on paper", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "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 fofr/flux-handwriting 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": "786bc82c11569935506ad1d9ae1b712c0a274cc4b75c23d2d9bd42e232540f1e", "input": { "model": "dev", "prompt": "HWRIT handwriting saying \\"Hello, this is a handrwriting lora\\", messy style, blue ink on paper", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 80, "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": "2024-12-14T12:00:45.658069Z", "created_at": "2024-12-14T12:00:38.074000Z", "data_removed": false, "error": null, "id": "7qc3px66q9rma0ckrm5ahx0bqw", "input": { "model": "dev", "prompt": "HWRIT handwriting saying \"Hello, this is a handrwriting lora\", messy style, blue ink on paper", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2024-12-14 12:00:38.739 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2024-12-14 12:00:38.740 | 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, 2818.32it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2713.85it/s]\n2024-12-14 12:00:38.852 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s\nfree=28625520238592\nDownloading weights\n2024-12-14T12:00:38Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpbhe_ng3e/weights url=https://replicate.delivery/xezq/xZRxaJALQcpfMalp2QtYfcAoJ4pHl4xDfwTpimS7OXhFlk1nA/trained_model.tar\n2024-12-14T12:00:39Z | INFO | [ Complete ] dest=/tmp/tmpbhe_ng3e/weights size=\"172 MB\" total_elapsed=0.562s url=https://replicate.delivery/xezq/xZRxaJALQcpfMalp2QtYfcAoJ4pHl4xDfwTpimS7OXhFlk1nA/trained_model.tar\nDownloaded weights in 0.59s\n2024-12-14 12:00:39.442 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/c3399d28a5b321f6\n2024-12-14 12:00:39.518 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2024-12-14 12:00:39.518 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2024-12-14 12:00:39.519 | 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, 2819.67it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2714.94it/s]\n2024-12-14 12:00:39.631 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s\nUsing seed: 14367\n0it [00:00, ?it/s]\n1it [00:00, 8.40it/s]\n2it [00:00, 5.87it/s]\n3it [00:00, 5.36it/s]\n4it [00:00, 5.15it/s]\n5it [00:00, 5.02it/s]\n6it [00:01, 4.93it/s]\n7it [00:01, 4.90it/s]\n8it [00:01, 4.88it/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, 4.82it/s]\n16it [00:03, 4.82it/s]\n17it [00:03, 4.81it/s]\n18it [00:03, 4.81it/s]\n19it [00:03, 4.81it/s]\n20it [00:04, 4.81it/s]\n21it [00:04, 4.82it/s]\n22it [00:04, 4.82it/s]\n23it [00:04, 4.82it/s]\n24it [00:04, 4.81it/s]\n25it [00:05, 4.81it/s]\n26it [00:05, 4.81it/s]\n27it [00:05, 4.81it/s]\n28it [00:05, 4.82it/s]\n28it [00:05, 4.89it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 6.9174548829999996, "total_time": 7.584069 }, "output": [ "https://replicate.delivery/xezq/OCjL5EeBDzUXNyrCX6q9z7exmhYW4qfVTJJKQCEkjev1WJrPB/out-0.jpg" ], "started_at": "2024-12-14T12:00:38.740614Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-brs4oie5w7hlxj6ekx2zcjjbetssqvtjwprbssmatmis4l2lijwq", "get": "https://api.replicate.com/v1/predictions/7qc3px66q9rma0ckrm5ahx0bqw", "cancel": "https://api.replicate.com/v1/predictions/7qc3px66q9rma0ckrm5ahx0bqw/cancel" }, "version": "786bc82c11569935506ad1d9ae1b712c0a274cc4b75c23d2d9bd42e232540f1e" }Generated in2024-12-14 12:00:38.739 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2024-12-14 12:00:38.740 | 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, 2818.32it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2713.85it/s] 2024-12-14 12:00:38.852 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s free=28625520238592 Downloading weights 2024-12-14T12:00:38Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpbhe_ng3e/weights url=https://replicate.delivery/xezq/xZRxaJALQcpfMalp2QtYfcAoJ4pHl4xDfwTpimS7OXhFlk1nA/trained_model.tar 2024-12-14T12:00:39Z | INFO | [ Complete ] dest=/tmp/tmpbhe_ng3e/weights size="172 MB" total_elapsed=0.562s url=https://replicate.delivery/xezq/xZRxaJALQcpfMalp2QtYfcAoJ4pHl4xDfwTpimS7OXhFlk1nA/trained_model.tar Downloaded weights in 0.59s 2024-12-14 12:00:39.442 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/c3399d28a5b321f6 2024-12-14 12:00:39.518 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2024-12-14 12:00:39.518 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2024-12-14 12:00:39.519 | 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, 2819.67it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2714.94it/s] 2024-12-14 12:00:39.631 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s Using seed: 14367 0it [00:00, ?it/s] 1it [00:00, 8.40it/s] 2it [00:00, 5.87it/s] 3it [00:00, 5.36it/s] 4it [00:00, 5.15it/s] 5it [00:00, 5.02it/s] 6it [00:01, 4.93it/s] 7it [00:01, 4.90it/s] 8it [00:01, 4.88it/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, 4.82it/s] 16it [00:03, 4.82it/s] 17it [00:03, 4.81it/s] 18it [00:03, 4.81it/s] 19it [00:03, 4.81it/s] 20it [00:04, 4.81it/s] 21it [00:04, 4.82it/s] 22it [00:04, 4.82it/s] 23it [00:04, 4.82it/s] 24it [00:04, 4.81it/s] 25it [00:05, 4.81it/s] 26it [00:05, 4.81it/s] 27it [00:05, 4.81it/s] 28it [00:05, 4.82it/s] 28it [00:05, 4.89it/s] Total safe images: 1 out of 1Prediction
fofr/flux-handwriting:786bc82c11569935506ad1d9ae1b712c0a274cc4b75c23d2d9bd42e232540f1eIDvdpr2266phrm80ckrm5at439f8StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- HWRIT handwriting saying "Hello, this is a handrwriting lora", messy style, blue ink on paper
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- jpg
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "HWRIT handwriting saying \"Hello, this is a handrwriting lora\", messy style, blue ink on paper", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "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 replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/flux-handwriting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-handwriting:786bc82c11569935506ad1d9ae1b712c0a274cc4b75c23d2d9bd42e232540f1e", { input: { model: "dev", prompt: "HWRIT handwriting saying \"Hello, this is a handrwriting lora\", messy style, blue ink on paper", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "jpg", 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 replicateImport the client:import replicateRun fofr/flux-handwriting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-handwriting:786bc82c11569935506ad1d9ae1b712c0a274cc4b75c23d2d9bd42e232540f1e", input={ "model": "dev", "prompt": "HWRIT handwriting saying \"Hello, this is a handrwriting lora\", messy style, blue ink on paper", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "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 fofr/flux-handwriting 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": "786bc82c11569935506ad1d9ae1b712c0a274cc4b75c23d2d9bd42e232540f1e", "input": { "model": "dev", "prompt": "HWRIT handwriting saying \\"Hello, this is a handrwriting lora\\", messy style, blue ink on paper", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 80, "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": "2024-12-14T12:00:45.141930Z", "created_at": "2024-12-14T12:00:38.068000Z", "data_removed": false, "error": null, "id": "vdpr2266phrm80ckrm5at439f8", "input": { "model": "dev", "prompt": "HWRIT handwriting saying \"Hello, this is a handrwriting lora\", messy style, blue ink on paper", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2024-12-14 12:00:38.712 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2024-12-14 12:00:38.712 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2743.51it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2662.37it/s]\n2024-12-14 12:00:38.827 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s\n2024-12-14 12:00:38.829 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/c3399d28a5b321f6\n2024-12-14 12:00:38.944 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2024-12-14 12:00:38.944 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2024-12-14 12:00:38.944 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2746.79it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2665.22it/s]\n2024-12-14 12:00:39.059 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s\nUsing seed: 64929\n0it [00:00, ?it/s]\n1it [00:00, 8.32it/s]\n2it [00:00, 5.81it/s]\n3it [00:00, 5.29it/s]\n4it [00:00, 5.09it/s]\n5it [00:00, 4.97it/s]\n6it [00:01, 4.89it/s]\n7it [00:01, 4.84it/s]\n8it [00:01, 4.82it/s]\n9it [00:01, 4.81it/s]\n10it [00:02, 4.80it/s]\n11it [00:02, 4.78it/s]\n12it [00:02, 4.77it/s]\n13it [00:02, 4.76it/s]\n14it [00:02, 4.76it/s]\n15it [00:03, 4.77it/s]\n16it [00:03, 4.77it/s]\n17it [00:03, 4.77it/s]\n18it [00:03, 4.77it/s]\n19it [00:03, 4.77it/s]\n20it [00:04, 4.78it/s]\n21it [00:04, 4.77it/s]\n22it [00:04, 4.77it/s]\n23it [00:04, 4.77it/s]\n24it [00:04, 4.76it/s]\n25it [00:05, 4.77it/s]\n26it [00:05, 4.76it/s]\n27it [00:05, 4.76it/s]\n28it [00:05, 4.75it/s]\n28it [00:05, 4.84it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 6.429392834, "total_time": 7.07393 }, "output": [ "https://replicate.delivery/xezq/TdJMamwtnBKdKlugMw8jMSA3MhThT714NIumaNvKhxe2KZ9JA/out-0.jpg" ], "started_at": "2024-12-14T12:00:38.712537Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-n5wm2dzf2ypt3zdyg7d65q7ygjxrcjibue76evw7uku4cizcwcya", "get": "https://api.replicate.com/v1/predictions/vdpr2266phrm80ckrm5at439f8", "cancel": "https://api.replicate.com/v1/predictions/vdpr2266phrm80ckrm5at439f8/cancel" }, "version": "786bc82c11569935506ad1d9ae1b712c0a274cc4b75c23d2d9bd42e232540f1e" }Generated in2024-12-14 12:00:38.712 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2024-12-14 12:00:38.712 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2743.51it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2662.37it/s] 2024-12-14 12:00:38.827 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s 2024-12-14 12:00:38.829 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/c3399d28a5b321f6 2024-12-14 12:00:38.944 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2024-12-14 12:00:38.944 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2024-12-14 12:00:38.944 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2746.79it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2665.22it/s] 2024-12-14 12:00:39.059 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s Using seed: 64929 0it [00:00, ?it/s] 1it [00:00, 8.32it/s] 2it [00:00, 5.81it/s] 3it [00:00, 5.29it/s] 4it [00:00, 5.09it/s] 5it [00:00, 4.97it/s] 6it [00:01, 4.89it/s] 7it [00:01, 4.84it/s] 8it [00:01, 4.82it/s] 9it [00:01, 4.81it/s] 10it [00:02, 4.80it/s] 11it [00:02, 4.78it/s] 12it [00:02, 4.77it/s] 13it [00:02, 4.76it/s] 14it [00:02, 4.76it/s] 15it [00:03, 4.77it/s] 16it [00:03, 4.77it/s] 17it [00:03, 4.77it/s] 18it [00:03, 4.77it/s] 19it [00:03, 4.77it/s] 20it [00:04, 4.78it/s] 21it [00:04, 4.77it/s] 22it [00:04, 4.77it/s] 23it [00:04, 4.77it/s] 24it [00:04, 4.76it/s] 25it [00:05, 4.77it/s] 26it [00:05, 4.76it/s] 27it [00:05, 4.76it/s] 28it [00:05, 4.75it/s] 28it [00:05, 4.84it/s] Total safe images: 1 out of 1
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