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openai / glide-text2im
Photorealistic Image Generation and Editing
Prediction
openai/glide-text2im:0edd79a209d37f1577d2462f98f014e9faba87d64a764f7d33078b22a2906462IDlk5drtin4jh4rg52kf72l7mpxeStatusSucceededSourceWebHardware–Total durationCreatedInput
- mode
- clip_guided
- prompt
- an oil painting of a corgi
{ "mode": "clip_guided", "prompt": "an oil painting of a corgi" }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 openai/glide-text2im using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "openai/glide-text2im:0edd79a209d37f1577d2462f98f014e9faba87d64a764f7d33078b22a2906462", { input: { mode: "clip_guided", prompt: "an oil painting of a corgi" } } ); console.log(output);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 openai/glide-text2im using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "openai/glide-text2im:0edd79a209d37f1577d2462f98f014e9faba87d64a764f7d33078b22a2906462", input={ "mode": "clip_guided", "prompt": "an oil painting of a corgi" } ) # The openai/glide-text2im model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/openai/glide-text2im/api#output-schema print(item)To learn more, take a look at the guide on getting started with Python.
Run openai/glide-text2im 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": "openai/glide-text2im:0edd79a209d37f1577d2462f98f014e9faba87d64a764f7d33078b22a2906462", "input": { "mode": "clip_guided", "prompt": "an oil painting of a corgi" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/openai/glide-text2im@sha256:0edd79a209d37f1577d2462f98f014e9faba87d64a764f7d33078b22a2906462 \ -i 'mode="clip_guided"' \ -i 'prompt="an oil painting of a corgi"'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/openai/glide-text2im@sha256:0edd79a209d37f1577d2462f98f014e9faba87d64a764f7d33078b22a2906462curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "mode": "clip_guided", "prompt": "an oil painting of a corgi" } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2022-01-01T14:23:31.711286Z", "created_at": "2022-01-01T14:23:11.346680Z", "data_removed": false, "error": null, "id": "lk5drtin4jh4rg52kf72l7mpxe", "input": { "mode": "clip_guided", "prompt": "an oil painting of a corgi" }, "logs": "\n 0%| | 0/100 [00:00<?, ?it/s]\n 1%| | 1/100 [00:00<00:15, 6.26it/s]\n 2%|▏ | 2/100 [00:00<00:16, 5.98it/s]\n 3%|▎ | 3/100 [00:00<00:15, 6.17it/s]\n 4%|▍ | 4/100 [00:00<00:15, 6.39it/s]\n 5%|▌ | 5/100 [00:00<00:14, 6.52it/s]\n 6%|▌ | 6/100 [00:00<00:14, 6.56it/s]\n 7%|▋ | 7/100 [00:01<00:14, 6.62it/s]\n 8%|▊ | 8/100 [00:01<00:13, 6.74it/s]\n 9%|▉ | 9/100 [00:01<00:13, 6.83it/s]\n 10%|█ | 10/100 [00:01<00:13, 6.78it/s]\n 11%|█ | 11/100 [00:01<00:13, 6.80it/s]\n 12%|█▏ | 12/100 [00:01<00:12, 6.79it/s]\n 13%|█▎ | 13/100 [00:01<00:12, 6.77it/s]\n 14%|█▍ | 14/100 [00:02<00:12, 6.86it/s]\n 15%|█▌ | 15/100 [00:02<00:12, 6.88it/s]\n 16%|█▌ | 16/100 [00:02<00:12, 6.91it/s]\n 17%|█▋ | 17/100 [00:02<00:12, 6.79it/s]\n 18%|█▊ | 18/100 [00:02<00:12, 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openai/glide-text2im:0edd79a209d37f1577d2462f98f014e9faba87d64a764f7d33078b22a2906462ID7j4fvnxhs5dgfpldjmqpyokk34StatusSucceededSourceWebHardware–Total durationCreatedInput
- mode
- text2im
- prompt
- an oil painting of a corgi
{ "mode": "text2im", "prompt": "an oil painting of a corgi" }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 openai/glide-text2im using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "openai/glide-text2im:0edd79a209d37f1577d2462f98f014e9faba87d64a764f7d33078b22a2906462", { input: { mode: "text2im", prompt: "an oil painting of a corgi" } } ); console.log(output);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 openai/glide-text2im using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "openai/glide-text2im:0edd79a209d37f1577d2462f98f014e9faba87d64a764f7d33078b22a2906462", input={ "mode": "text2im", "prompt": "an oil painting of a corgi" } ) # The openai/glide-text2im model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/openai/glide-text2im/api#output-schema print(item)To learn more, take a look at the guide on getting started with Python.
Run openai/glide-text2im 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": "openai/glide-text2im:0edd79a209d37f1577d2462f98f014e9faba87d64a764f7d33078b22a2906462", "input": { "mode": "text2im", "prompt": "an oil painting of a corgi" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/openai/glide-text2im@sha256:0edd79a209d37f1577d2462f98f014e9faba87d64a764f7d33078b22a2906462 \ -i 'mode="text2im"' \ -i 'prompt="an oil painting of a corgi"'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/openai/glide-text2im@sha256:0edd79a209d37f1577d2462f98f014e9faba87d64a764f7d33078b22a2906462curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "mode": "text2im", "prompt": "an oil painting of a corgi" } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2022-01-01T14:19:39.276865Z", "created_at": "2022-01-01T14:19:23.718832Z", "data_removed": false, "error": null, "id": "7j4fvnxhs5dgfpldjmqpyokk34", "input": { "mode": "text2im", "prompt": "an oil painting of a corgi" }, "logs": "\n 0%| | 0/100 [00:00<?, ?it/s]\n 1%| | 1/100 [00:00<00:13, 7.54it/s]\n 2%|▏ | 2/100 [00:00<00:12, 7.69it/s]\n 3%|▎ | 3/100 [00:00<00:11, 8.25it/s]\n 4%|▍ | 4/100 [00:00<00:11, 8.67it/s]\n 5%|▌ | 5/100 [00:00<00:10, 8.95it/s]\n 6%|▌ | 6/100 [00:00<00:10, 9.09it/s]\n 7%|▋ | 7/100 [00:00<00:10, 9.20it/s]\n 8%|▊ | 8/100 [00:00<00:09, 9.27it/s]\n 9%|▉ | 9/100 [00:00<00:09, 9.47it/s]\n 10%|█ | 10/100 [00:01<00:09, 9.50it/s]\n 11%|█ | 11/100 [00:01<00:09, 9.45it/s]\n 13%|█▎ | 13/100 [00:01<00:08, 9.71it/s]\n 15%|█▌ | 15/100 [00:01<00:08, 9.83it/s]\n 16%|█▌ | 16/100 [00:01<00:08, 9.74it/s]\n 17%|█▋ | 17/100 [00:01<00:08, 9.65it/s]\n 18%|█▊ | 18/100 [00:01<00:08, 9.60it/s]\n 19%|█▉ | 19/100 [00:02<00:08, 9.63it/s]\n 21%|██ | 21/100 [00:02<00:08, 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6.10it/s]\n 81%|████████▏ | 22/27 [00:03<00:00, 6.11it/s]\n 85%|████████▌ | 23/27 [00:03<00:00, 6.14it/s]\n 89%|████████▉ | 24/27 [00:03<00:00, 6.16it/s]\n 93%|█████████▎| 25/27 [00:04<00:00, 6.16it/s]\n 96%|█████████▋| 26/27 [00:04<00:00, 6.15it/s]\n100%|██████████| 27/27 [00:04<00:00, 6.16it/s]\n100%|██████████| 27/27 [00:04<00:00, 6.22it/s]", "metrics": { "predict_time": 15.332288, "total_time": 15.558033 }, "output": [ { "file": "https://replicate.delivery/mgxm/a1201519-e30f-421f-adf4-b80d536491e0/out.png" } ], "started_at": "2022-01-01T14:19:23.944577Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/7j4fvnxhs5dgfpldjmqpyokk34", "cancel": "https://api.replicate.com/v1/predictions/7j4fvnxhs5dgfpldjmqpyokk34/cancel" }, "version": "0edd79a209d37f1577d2462f98f014e9faba87d64a764f7d33078b22a2906462" }Generated in0%| | 0/100 [00:00<?, ?it/s] 1%| | 1/100 [00:00<00:13, 7.54it/s] 2%|▏ | 2/100 [00:00<00:12, 7.69it/s] 3%|▎ | 3/100 [00:00<00:11, 8.25it/s] 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openai/glide-text2im:0edd79a209d37f1577d2462f98f014e9faba87d64a764f7d33078b22a2906462IDx5olt2qt4jfpvlkpj2bo5bmgtqStatusSucceededSourceWebHardware–Total durationCreatedInput
- mode
- inpaint
- image
- prompt
- an oil painting of a corgi
{ "mode": "inpaint", "image": "https://replicate.delivery/mgxm/520d0124-3528-4ffe-ad21-e1159670f125/grass.png", "prompt": "an oil painting of a corgi" }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 openai/glide-text2im using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "openai/glide-text2im:0edd79a209d37f1577d2462f98f014e9faba87d64a764f7d33078b22a2906462", { input: { mode: "inpaint", image: "https://replicate.delivery/mgxm/520d0124-3528-4ffe-ad21-e1159670f125/grass.png", prompt: "an oil painting of a corgi" } } ); console.log(output);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 openai/glide-text2im using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "openai/glide-text2im:0edd79a209d37f1577d2462f98f014e9faba87d64a764f7d33078b22a2906462", input={ "mode": "inpaint", "image": "https://replicate.delivery/mgxm/520d0124-3528-4ffe-ad21-e1159670f125/grass.png", "prompt": "an oil painting of a corgi" } ) # The openai/glide-text2im model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/openai/glide-text2im/api#output-schema print(item)To learn more, take a look at the guide on getting started with Python.
Run openai/glide-text2im 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": "openai/glide-text2im:0edd79a209d37f1577d2462f98f014e9faba87d64a764f7d33078b22a2906462", "input": { "mode": "inpaint", "image": "https://replicate.delivery/mgxm/520d0124-3528-4ffe-ad21-e1159670f125/grass.png", "prompt": "an oil painting of a corgi" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/openai/glide-text2im@sha256:0edd79a209d37f1577d2462f98f014e9faba87d64a764f7d33078b22a2906462 \ -i 'mode="inpaint"' \ -i 'image="https://replicate.delivery/mgxm/520d0124-3528-4ffe-ad21-e1159670f125/grass.png"' \ -i 'prompt="an oil painting of a corgi"'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/openai/glide-text2im@sha256:0edd79a209d37f1577d2462f98f014e9faba87d64a764f7d33078b22a2906462curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "mode": "inpaint", "image": "https://replicate.delivery/mgxm/520d0124-3528-4ffe-ad21-e1159670f125/grass.png", "prompt": "an oil painting of a corgi" } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2022-01-01T14:25:19.116226Z", "created_at": "2022-01-01T14:25:02.217311Z", "data_removed": false, "error": null, "id": "x5olt2qt4jfpvlkpj2bo5bmgtq", "input": { "mode": "inpaint", "image": "https://replicate.delivery/mgxm/520d0124-3528-4ffe-ad21-e1159670f125/grass.png", "prompt": "an oil painting of a corgi" }, "logs": "\n 0%| | 0/100 [00:00<?, ?it/s]\n 1%| | 1/100 [00:00<00:13, 7.20it/s]\n 2%|▏ | 2/100 [00:00<00:12, 7.60it/s]\n 3%|▎ | 3/100 [00:00<00:12, 7.97it/s]\n 4%|▍ | 4/100 [00:00<00:11, 8.45it/s]\n 6%|▌ | 6/100 [00:00<00:10, 8.90it/s]\n 7%|▋ | 7/100 [00:00<00:10, 9.18it/s]\n 9%|▉ | 9/100 [00:00<00:09, 9.44it/s]\n 11%|█ | 11/100 [00:01<00:09, 9.59it/s]\n 12%|█▏ | 12/100 [00:01<00:09, 9.60it/s]\n 13%|█▎ | 13/100 [00:01<00:09, 9.56it/s]\n 14%|█▍ | 14/100 [00:01<00:08, 9.60it/s]\n 15%|█▌ | 15/100 [00:01<00:08, 9.60it/s]\n 16%|█▌ | 16/100 [00:01<00:08, 9.64it/s]\n 17%|█▋ | 17/100 [00:01<00:08, 9.66it/s]\n 18%|█▊ | 18/100 [00:01<00:08, 9.66it/s]\n 19%|█▉ | 19/100 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48%|████▊ | 13/27 [00:02<00:02, 6.05it/s]\n 52%|█████▏ | 14/27 [00:02<00:02, 6.06it/s]\n 56%|█████▌ | 15/27 [00:02<00:01, 6.05it/s]\n 59%|█████▉ | 16/27 [00:02<00:01, 6.06it/s]\n 63%|██████▎ | 17/27 [00:02<00:01, 6.06it/s]\n 67%|██████▋ | 18/27 [00:02<00:01, 6.05it/s]\n 70%|███████ | 19/27 [00:03<00:01, 6.04it/s]\n 74%|███████▍ | 20/27 [00:03<00:01, 6.07it/s]\n 78%|███████▊ | 21/27 [00:03<00:00, 6.08it/s]\n 81%|████████▏ | 22/27 [00:03<00:00, 6.11it/s]\n 85%|████████▌ | 23/27 [00:03<00:00, 6.10it/s]\n 89%|████████▉ | 24/27 [00:03<00:00, 6.08it/s]\n 93%|█████████▎| 25/27 [00:04<00:00, 6.11it/s]\n 96%|█████████▋| 26/27 [00:04<00:00, 6.11it/s]\n100%|██████████| 27/27 [00:04<00:00, 6.08it/s]\n100%|██████████| 27/27 [00:04<00:00, 6.07it/s]", "metrics": { "predict_time": 16.324952, "total_time": 16.898915 }, "output": [ { "file": "https://replicate.delivery/mgxm/10cfaf56-9b9c-4cc5-8df5-d99b63e15891/out.png" } ], "started_at": "2022-01-01T14:25:02.791274Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/x5olt2qt4jfpvlkpj2bo5bmgtq", "cancel": "https://api.replicate.com/v1/predictions/x5olt2qt4jfpvlkpj2bo5bmgtq/cancel" }, "version": "0edd79a209d37f1577d2462f98f014e9faba87d64a764f7d33078b22a2906462" }Generated in0%| | 0/100 [00:00<?, ?it/s] 1%| | 1/100 [00:00<00:13, 7.20it/s] 2%|▏ | 2/100 [00:00<00:12, 7.60it/s] 3%|▎ | 3/100 [00:00<00:12, 7.97it/s] 4%|▍ | 4/100 [00:00<00:11, 8.45it/s] 6%|▌ | 6/100 [00:00<00:10, 8.90it/s] 7%|▋ | 7/100 [00:00<00:10, 9.18it/s] 9%|▉ | 9/100 [00:00<00:09, 9.44it/s] 11%|█ | 11/100 [00:01<00:09, 9.59it/s] 12%|█▏ | 12/100 [00:01<00:09, 9.60it/s] 13%|█▎ | 13/100 [00:01<00:09, 9.56it/s] 14%|█▍ | 14/100 [00:01<00:08, 9.60it/s] 15%|█▌ | 15/100 [00:01<00:08, 9.60it/s] 16%|█▌ | 16/100 [00:01<00:08, 9.64it/s] 17%|█▋ | 17/100 [00:01<00:08, 9.66it/s] 18%|█▊ | 18/100 [00:01<00:08, 9.66it/s] 19%|█▉ | 19/100 [00:01<00:08, 9.70it/s] 20%|██ | 20/100 [00:02<00:08, 9.59it/s] 21%|██ | 21/100 [00:02<00:08, 9.69it/s] 22%|██▏ | 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[00:09<00:00, 10.26it/s] 94%|█████████▍| 94/100 [00:09<00:00, 10.25it/s] 96%|█████████▌| 96/100 [00:09<00:00, 10.27it/s] 98%|█████████▊| 98/100 [00:09<00:00, 10.27it/s] 100%|██████████| 100/100 [00:10<00:00, 10.25it/s] 100%|██████████| 100/100 [00:10<00:00, 9.91it/s] 0%| | 0/27 [00:00<?, ?it/s] 4%|▎ | 1/27 [00:00<00:04, 6.04it/s] 7%|▋ | 2/27 [00:00<00:04, 6.05it/s] 11%|█ | 3/27 [00:00<00:03, 6.05it/s] 15%|█▍ | 4/27 [00:00<00:03, 6.06it/s] 19%|█▊ | 5/27 [00:00<00:03, 6.06it/s] 22%|██▏ | 6/27 [00:00<00:03, 6.07it/s] 26%|██▌ | 7/27 [00:01<00:03, 6.09it/s] 30%|██▉ | 8/27 [00:01<00:03, 6.10it/s] 33%|███▎ | 9/27 [00:01<00:02, 6.09it/s] 37%|███▋ | 10/27 [00:01<00:02, 6.03it/s] 41%|████ | 11/27 [00:01<00:02, 6.00it/s] 44%|████▍ | 12/27 [00:01<00:02, 6.02it/s] 48%|████▊ | 13/27 [00:02<00:02, 6.05it/s] 52%|█████▏ | 14/27 [00:02<00:02, 6.06it/s] 56%|█████▌ | 15/27 [00:02<00:01, 6.05it/s] 59%|█████▉ | 16/27 [00:02<00:01, 6.06it/s] 63%|██████▎ | 17/27 [00:02<00:01, 6.06it/s] 67%|██████▋ | 18/27 [00:02<00:01, 6.05it/s] 70%|███████ | 19/27 [00:03<00:01, 6.04it/s] 74%|███████▍ | 20/27 [00:03<00:01, 6.07it/s] 78%|███████▊ | 21/27 [00:03<00:00, 6.08it/s] 81%|████████▏ | 22/27 [00:03<00:00, 6.11it/s] 85%|████████▌ | 23/27 [00:03<00:00, 6.10it/s] 89%|████████▉ | 24/27 [00:03<00:00, 6.08it/s] 93%|█████████▎| 25/27 [00:04<00:00, 6.11it/s] 96%|█████████▋| 26/27 [00:04<00:00, 6.11it/s] 100%|██████████| 27/27 [00:04<00:00, 6.08it/s] 100%|██████████| 27/27 [00:04<00:00, 6.07it/s]
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