replicate
/
dreambooth
Train your own custom Stable Diffusion model using a small set of images
Prediction
replicate/dreambooth:a8ba568dInput
- seed
- 1337
- adam_beta1
- 0.9
- adam_beta2
- 0.999
- resolution
- 512
- adam_epsilon
- 1e-8
- class_prompt
- a cat
- lr_scheduler
- constant
- instance_data
- data.zip
- learning_rate
- 0.000001
- max_grad_norm
- 1
- n_save_sample
- 4
- use_8bit_adam
- instance_prompt
- a cjw cat
- max_train_steps
- 1000
- num_class_images
- 100
- num_train_epochs
- 1
- save_infer_steps
- 50
- train_batch_size
- 1
- adam_weight_decay
- 0.01
- prior_loss_weight
- 1
- sample_batch_size
- 4
- train_text_encoder
- save_guidance_scale
- 7.5
- gradient_checkpointing
- with_prior_preservation
- gradient_accumulation_steps
- 1
{ "seed": 1337, "adam_beta1": 0.9, "adam_beta2": 0.999, "resolution": 512, "adam_epsilon": 1e-8, "class_prompt": "a cat", "lr_scheduler": "constant", "instance_data": "https://replicate.delivery/pbxt/HlRmIY3SePK6D8ZgnTvgymRWRSFqJlrDrfxJjA6QAazg1wVl/data.zip", "learning_rate": 0.000001, "max_grad_norm": 1, "n_save_sample": 4, "use_8bit_adam": false, "instance_prompt": "a cjw cat", "max_train_steps": 1000, "num_class_images": 100, "num_train_epochs": 1, "save_infer_steps": 50, "train_batch_size": 1, "adam_weight_decay": 0.01, "prior_loss_weight": 1, "sample_batch_size": 4, "train_text_encoder": true, "save_guidance_scale": 7.5, "gradient_checkpointing": false, "with_prior_preservation": true, "gradient_accumulation_steps": 1 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run replicate/dreambooth using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "replicate/dreambooth:a8ba568da0313951a6b311b43b1ea3bf9f2ef7b9fd97ed94cebd7ffd2da66654", { input: { seed: 1337, adam_beta1: 0.9, adam_beta2: 0.999, resolution: 512, adam_epsilon: 1e-8, class_prompt: "a cat", lr_scheduler: "constant", instance_data: "https://replicate.delivery/pbxt/HlRmIY3SePK6D8ZgnTvgymRWRSFqJlrDrfxJjA6QAazg1wVl/data.zip", learning_rate: 0.000001, max_grad_norm: 1, n_save_sample: 4, use_8bit_adam: false, instance_prompt: "a cjw cat", max_train_steps: 1000, num_class_images: 100, num_train_epochs: 1, save_infer_steps: 50, train_batch_size: 1, adam_weight_decay: 0.01, prior_loss_weight: 1, sample_batch_size: 4, train_text_encoder: true, save_guidance_scale: 7.5, gradient_checkpointing: false, with_prior_preservation: true, gradient_accumulation_steps: 1 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run replicate/dreambooth using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "replicate/dreambooth:a8ba568da0313951a6b311b43b1ea3bf9f2ef7b9fd97ed94cebd7ffd2da66654", input={ "seed": 1337, "adam_beta1": 0.9, "adam_beta2": 0.999, "resolution": 512, "adam_epsilon": 1e-8, "class_prompt": "a cat", "lr_scheduler": "constant", "instance_data": "https://replicate.delivery/pbxt/HlRmIY3SePK6D8ZgnTvgymRWRSFqJlrDrfxJjA6QAazg1wVl/data.zip", "learning_rate": 0.000001, "max_grad_norm": 1, "n_save_sample": 4, "use_8bit_adam": False, "instance_prompt": "a cjw cat", "max_train_steps": 1000, "num_class_images": 100, "num_train_epochs": 1, "save_infer_steps": 50, "train_batch_size": 1, "adam_weight_decay": 0.01, "prior_loss_weight": 1, "sample_batch_size": 4, "train_text_encoder": True, "save_guidance_scale": 7.5, "gradient_checkpointing": False, "with_prior_preservation": True, "gradient_accumulation_steps": 1 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run replicate/dreambooth 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": "a8ba568da0313951a6b311b43b1ea3bf9f2ef7b9fd97ed94cebd7ffd2da66654", "input": { "seed": 1337, "adam_beta1": 0.9, "adam_beta2": 0.999, "resolution": 512, "adam_epsilon": 1e-8, "class_prompt": "a cat", "lr_scheduler": "constant", "instance_data": "https://replicate.delivery/pbxt/HlRmIY3SePK6D8ZgnTvgymRWRSFqJlrDrfxJjA6QAazg1wVl/data.zip", "learning_rate": 0.000001, "max_grad_norm": 1, "n_save_sample": 4, "use_8bit_adam": false, "instance_prompt": "a cjw cat", "max_train_steps": 1000, "num_class_images": 100, "num_train_epochs": 1, "save_infer_steps": 50, "train_batch_size": 1, "adam_weight_decay": 0.01, "prior_loss_weight": 1, "sample_batch_size": 4, "train_text_encoder": true, "save_guidance_scale": 7.5, "gradient_checkpointing": false, "with_prior_preservation": true, "gradient_accumulation_steps": 1 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-11-17T02:47:38.043848Z", "created_at": "2022-11-17T02:35:42.949173Z", "data_removed": false, "error": null, "id": "4yyxeqh2cfcd7pueymhl6jhcra", "input": { "seed": 1337, "adam_beta1": 0.9, "adam_beta2": 0.999, "resolution": 512, "adam_epsilon": 1e-8, "class_prompt": "a cat", "lr_scheduler": "constant", "instance_data": "https://replicate.delivery/pbxt/HlRmIY3SePK6D8ZgnTvgymRWRSFqJlrDrfxJjA6QAazg1wVl/data.zip", "learning_rate": 0.000001, "max_grad_norm": 1, "n_save_sample": 4, "use_8bit_adam": false, "instance_prompt": "a cjw cat", "max_train_steps": 1000, "num_class_images": 100, "num_train_epochs": 1, "save_infer_steps": 50, "train_batch_size": 1, "adam_weight_decay": 0.01, "prior_loss_weight": 1, "sample_batch_size": 4, "train_text_encoder": true, "save_guidance_scale": 7.5, "gradient_checkpointing": false, "with_prior_preservation": true, "gradient_accumulation_steps": 1 }, "logs": "/root/.pyenv/versions/3.10.8/lib/python3.10/site-packages/accelerate/accelerator.py:179: UserWarning: `log_with=tensorboard` was passed but no supported trackers are currently installed.\nwarnings.warn(f\"`log_with={log_with}` was passed but no supported trackers are currently installed.\")\nYou have passed `None` for safety_checker to disable its functionality in <class 'diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline'>. Note that this might lead to problems when using <class 'diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline'> and is not recommended.\nGenerating class images: 0%| | 0/25 [00:00<?, ?it/s]\nGenerating class images: 4%|▍ | 1/25 [00:26<10:25, 26.06s/it]\nGenerating class images: 8%|▊ | 2/25 [00:35<06:15, 16.32s/it]\nGenerating class images: 12%|█▏ | 3/25 [00:45<04:50, 13.20s/it]\nGenerating class images: 16%|█▌ | 4/25 [00:54<04:06, 11.74s/it]\nGenerating class images: 20%|██ | 5/25 [01:04<03:38, 10.92s/it]\nGenerating class images: 24%|██▍ | 6/25 [01:13<03:18, 10.44s/it]\nGenerating class images: 28%|██▊ | 7/25 [01:22<03:02, 10.13s/it]\nGenerating class images: 32%|███▏ | 8/25 [01:32<02:48, 9.93s/it]\nGenerating class images: 36%|███▌ | 9/25 [01:41<02:36, 9.79s/it]\nGenerating class images: 40%|████ | 10/25 [01:51<02:25, 9.69s/it]\nGenerating class images: 44%|████▍ | 11/25 [02:00<02:14, 9.63s/it]\nGenerating class images: 48%|████▊ | 12/25 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100%|██████████| 1000/1000 [06:05<00:00, 2.83it/s, loss=0.282, lr=1e-6]You have passed `None` for safety_checker to disable its functionality in <class 'diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline'>. Note that this might lead to problems when using <class 'diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline'> and is not recommended.\n[*] Weights saved at checkpoints\nSteps: 100%|██████████| 1000/1000 [06:09<00:00, 2.71it/s, loss=0.282, lr=1e-6]\nThu Nov 17 02:47:06 2022\n+-----------------------------------------------------------------------------+\n| NVIDIA-SMI 510.47.03 Driver Version: 510.47.03 CUDA Version: 11.6 |\n|-------------------------------+----------------------+----------------------+\n| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\n| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\n| | | MIG M. |\n|===============================+======================+======================|\n| 0 NVIDIA A100-SXM... Off | 00000000:00:04.0 Off | 0 |\n| N/A 39C P0 58W / 400W | 2122MiB / 40960MiB | 15% Default |\n| | | Disabled |\n+-------------------------------+----------------------+----------------------+\n+-----------------------------------------------------------------------------+\n| Processes: |\n| GPU GI CI PID Type Process name GPU Memory |\n| ID ID Usage |\n|=============================================================================|\n| 0 N/A N/A 399088 C 2119MiB |\n+-----------------------------------------------------------------------------+\ncheckpoints/tokenizer\ncheckpoints/unet\ncheckpoints/vae\ncheckpoints/text_encoder\ncheckpoints/feature_extractor\ncheckpoints/args.json\ncheckpoints/model_index.json\ncheckpoints/scheduler\ncheckpoints/tokenizer/vocab.json\ncheckpoints/tokenizer/special_tokens_map.json\ncheckpoints/tokenizer/merges.txt\ncheckpoints/tokenizer/tokenizer_config.json\ncheckpoints/unet/diffusion_pytorch_model.bin\ncheckpoints/unet/config.json\ncheckpoints/vae/diffusion_pytorch_model.bin\ncheckpoints/vae/config.json\ncheckpoints/text_encoder/pytorch_model.bin\ncheckpoints/text_encoder/config.json\ncheckpoints/feature_extractor/preprocessor_config.json\ncheckpoints/scheduler/scheduler_config.json", "metrics": { "predict_time": 691.719585, "total_time": 715.094675 }, "output": "https://replicate.delivery/pbxt/g72ns6cGvjIzPlqpwcCFjDPjyZfLocdvgqcMj1Uwy6ZZlaAIA/output.zip", "started_at": "2022-11-17T02:36:06.324263Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/4yyxeqh2cfcd7pueymhl6jhcra", "cancel": "https://api.replicate.com/v1/predictions/4yyxeqh2cfcd7pueymhl6jhcra/cancel" }, "version": "7198ab665a5e793fc8d89ed80db7660cc5fdd086f2809c19d5a88ec5dbcadf99" }
Generated in/root/.pyenv/versions/3.10.8/lib/python3.10/site-packages/accelerate/accelerator.py:179: UserWarning: `log_with=tensorboard` was passed but no supported trackers are currently installed. warnings.warn(f"`log_with={log_with}` was passed but no supported trackers are currently installed.") You have passed `None` for safety_checker to disable its functionality in <class 'diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline'>. Note that this might lead to problems when using <class 'diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline'> and is not recommended. 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[06:02<00:02, 2.81it/s, loss=0.282, lr=1e-6] Steps: 99%|█████████▉| 994/1000 [06:03<00:02, 2.81it/s, loss=0.282, lr=1e-6] Steps: 100%|█████████▉| 995/1000 [06:03<00:01, 2.83it/s, loss=0.282, lr=1e-6] Steps: 100%|█████████▉| 996/1000 [06:03<00:01, 2.84it/s, loss=0.282, lr=1e-6] Steps: 100%|█████████▉| 997/1000 [06:04<00:01, 2.86it/s, loss=0.282, lr=1e-6] Steps: 100%|█████████▉| 998/1000 [06:04<00:00, 2.85it/s, loss=0.282, lr=1e-6] Steps: 100%|█████████▉| 999/1000 [06:05<00:00, 2.83it/s, loss=0.282, lr=1e-6] Steps: 100%|██████████| 1000/1000 [06:05<00:00, 2.83it/s, loss=0.282, lr=1e-6]You have passed `None` for safety_checker to disable its functionality in <class 'diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline'>. Note that this might lead to problems when using <class 'diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline'> and is not recommended. [*] Weights saved at checkpoints Steps: 100%|██████████| 1000/1000 [06:09<00:00, 2.71it/s, loss=0.282, lr=1e-6] Thu Nov 17 02:47:06 2022 +-----------------------------------------------------------------------------+ | NVIDIA-SMI 510.47.03 Driver Version: 510.47.03 CUDA Version: 11.6 | |-------------------------------+----------------------+----------------------+ | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |===============================+======================+======================| | 0 NVIDIA A100-SXM... Off | 00000000:00:04.0 Off | 0 | | N/A 39C P0 58W / 400W | 2122MiB / 40960MiB | 15% Default | | | | Disabled | +-------------------------------+----------------------+----------------------+ +-----------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=============================================================================| | 0 N/A N/A 399088 C 2119MiB | +-----------------------------------------------------------------------------+ checkpoints/tokenizer checkpoints/unet checkpoints/vae checkpoints/text_encoder checkpoints/feature_extractor checkpoints/args.json checkpoints/model_index.json checkpoints/scheduler checkpoints/tokenizer/vocab.json checkpoints/tokenizer/special_tokens_map.json checkpoints/tokenizer/merges.txt checkpoints/tokenizer/tokenizer_config.json checkpoints/unet/diffusion_pytorch_model.bin checkpoints/unet/config.json checkpoints/vae/diffusion_pytorch_model.bin checkpoints/vae/config.json checkpoints/text_encoder/pytorch_model.bin checkpoints/text_encoder/config.json checkpoints/feature_extractor/preprocessor_config.json checkpoints/scheduler/scheduler_config.json
Prediction
replicate/dreambooth:a8ba568dInput
- class_prompt
- a photo of a man
- instance_data
- data.zip
- instance_prompt
- a photo of bfirsh
- max_train_steps
- 2000
{ "class_prompt": "a photo of a man", "instance_data": "https://replicate.delivery/pbxt/HoUeWsrtTTCJEpKGdLKqIYTfo8nbUTSNs565MkGxEstjfwKt/data.zip", "instance_prompt": "a photo of bfirsh", "max_train_steps": 2000 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run replicate/dreambooth using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "replicate/dreambooth:a8ba568da0313951a6b311b43b1ea3bf9f2ef7b9fd97ed94cebd7ffd2da66654", { input: { class_prompt: "a photo of a man", instance_data: "https://replicate.delivery/pbxt/HoUeWsrtTTCJEpKGdLKqIYTfo8nbUTSNs565MkGxEstjfwKt/data.zip", instance_prompt: "a photo of bfirsh", max_train_steps: 2000 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run replicate/dreambooth using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "replicate/dreambooth:a8ba568da0313951a6b311b43b1ea3bf9f2ef7b9fd97ed94cebd7ffd2da66654", input={ "class_prompt": "a photo of a man", "instance_data": "https://replicate.delivery/pbxt/HoUeWsrtTTCJEpKGdLKqIYTfo8nbUTSNs565MkGxEstjfwKt/data.zip", "instance_prompt": "a photo of bfirsh", "max_train_steps": 2000 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run replicate/dreambooth 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": "a8ba568da0313951a6b311b43b1ea3bf9f2ef7b9fd97ed94cebd7ffd2da66654", "input": { "class_prompt": "a photo of a man", "instance_data": "https://replicate.delivery/pbxt/HoUeWsrtTTCJEpKGdLKqIYTfo8nbUTSNs565MkGxEstjfwKt/data.zip", "instance_prompt": "a photo of bfirsh", "max_train_steps": 2000 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-11-20T21:14:09.942760Z", "created_at": "2022-11-20T20:56:43.273832Z", "data_removed": false, "error": null, "id": "h3wipflhzrexbasf3ngae6em64", "input": { "class_prompt": "a photo of a man", "instance_data": "https://replicate.delivery/pbxt/HoUeWsrtTTCJEpKGdLKqIYTfo8nbUTSNs565MkGxEstjfwKt/data.zip", "instance_prompt": "a photo of bfirsh", "max_train_steps": 2000 }, "logs": "/root/.pyenv/versions/3.10.8/lib/python3.10/site-packages/accelerate/accelerator.py:179: UserWarning: `log_with=tensorboard` was passed but no supported trackers are currently installed.\nwarnings.warn(f\"`log_with={log_with}` was passed but no supported trackers are currently installed.\")\nYou have passed `None` for safety_checker to disable its functionality in <class 'diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline'>. Note that this might lead to problems when using <class 'diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline'> and is not recommended.\nGenerating class images: 0%| | 0/13 [00:00<?, ?it/s]\nGenerating class images: 8%|▊ | 1/13 [00:42<08:28, 42.41s/it]\nGenerating class images: 15%|█▌ | 2/13 [00:51<04:13, 23.06s/it]\nGenerating class images: 23%|██▎ | 3/13 [01:01<02:48, 16.87s/it]\nGenerating class images: 31%|███ | 4/13 [01:10<02:05, 13.97s/it]\nGenerating class images: 38%|███▊ | 5/13 [01:20<01:39, 12.43s/it]\nGenerating class images: 46%|████▌ | 6/13 [01:30<01:20, 11.43s/it]\nGenerating class images: 54%|█████▍ | 7/13 [01:39<01:04, 10.80s/it]\nGenerating class images: 62%|██████▏ | 8/13 [01:49<00:51, 10.38s/it]\nGenerating class images: 69%|██████▉ | 9/13 [01:58<00:40, 10.10s/it]\nGenerating class images: 77%|███████▋ | 10/13 [02:08<00:29, 9.91s/it]\nGenerating class images: 85%|████████▍ | 11/13 [02:17<00:19, 9.78s/it]\nGenerating class images: 92%|█████████▏| 12/13 [02:27<00:09, 9.69s/it]\nGenerating class images: 100%|██████████| 13/13 [02:41<00:00, 11.19s/it]\nGenerating class images: 100%|██████████| 13/13 [02:41<00:00, 12.44s/it]\nCaching latents: 0%| | 0/50 [00:00<?, ?it/s]\nCaching latents: 2%|▏ | 1/50 [00:01<00:49, 1.00s/it]\nCaching latents: 4%|▍ | 2/50 [00:01<00:24, 1.94it/s]\nCaching latents: 10%|█ | 5/50 [00:01<00:07, 5.69it/s]\nCaching latents: 16%|█▌ | 8/50 [00:01<00:04, 9.45it/s]\nCaching latents: 22%|██▏ | 11/50 [00:01<00:03, 12.71it/s]\nCaching latents: 28%|██▊ | 14/50 [00:01<00:02, 15.95it/s]\nCaching latents: 34%|███▍ | 17/50 [00:01<00:02, 14.63it/s]\nCaching latents: 40%|████ | 20/50 [00:01<00:01, 17.54it/s]\nCaching latents: 46%|████▌ | 23/50 [00:02<00:01, 15.88it/s]\nCaching latents: 52%|█████▏ | 26/50 [00:02<00:01, 18.53it/s]\nCaching latents: 58%|█████▊ | 29/50 [00:02<00:01, 20.86it/s]\nCaching latents: 64%|██████▍ | 32/50 [00:02<00:01, 17.87it/s]\nCaching latents: 70%|███████ | 35/50 [00:02<00:00, 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[11:55<00:01, 2.88it/s, loss=0.279, lr=1e-6]\nSteps: 100%|█████████▉| 1998/2000 [11:55<00:00, 2.87it/s, loss=0.279, lr=1e-6]\nSteps: 100%|█████████▉| 1999/2000 [11:56<00:00, 2.88it/s, loss=0.279, lr=1e-6]\nSteps: 100%|██████████| 2000/2000 [11:56<00:00, 2.89it/s, loss=0.279, lr=1e-6]You have passed `None` for safety_checker to disable its functionality in <class 'diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline'>. Note that this might lead to problems when using <class 'diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline'> and is not recommended.\n[*] Weights saved at checkpoints\nSteps: 100%|██████████| 2000/2000 [12:01<00:00, 2.77it/s, loss=0.279, lr=1e-6]\nSun Nov 20 21:13:41 2022\n+-----------------------------------------------------------------------------+\n| NVIDIA-SMI 510.47.03 Driver Version: 510.47.03 CUDA Version: 11.6 |\n|-------------------------------+----------------------+----------------------+\n| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\n| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\n| | | MIG M. |\n|===============================+======================+======================|\n| 0 NVIDIA A100-SXM... Off | 00000000:00:04.0 Off | 0 |\n| N/A 38C P0 50W / 400W | 2122MiB / 40960MiB | 11% Default |\n| | | Disabled |\n+-------------------------------+----------------------+----------------------+\n+-----------------------------------------------------------------------------+\n| Processes: |\n| GPU GI CI PID Type Process name GPU Memory |\n| ID ID Usage |\n|=============================================================================|\n| 0 N/A N/A 343420 C 2119MiB |\n+-----------------------------------------------------------------------------+\ncheckpoints/tokenizer\ncheckpoints/unet\ncheckpoints/vae\ncheckpoints/text_encoder\ncheckpoints/feature_extractor\ncheckpoints/args.json\ncheckpoints/model_index.json\ncheckpoints/scheduler\ncheckpoints/tokenizer/vocab.json\ncheckpoints/tokenizer/special_tokens_map.json\ncheckpoints/tokenizer/merges.txt\ncheckpoints/tokenizer/tokenizer_config.json\ncheckpoints/unet/diffusion_pytorch_model.bin\ncheckpoints/unet/config.json\ncheckpoints/vae/diffusion_pytorch_model.bin\ncheckpoints/vae/config.json\ncheckpoints/text_encoder/pytorch_model.bin\ncheckpoints/text_encoder/config.json\ncheckpoints/feature_extractor/preprocessor_config.json\ncheckpoints/scheduler/scheduler_config.json", "metrics": { "predict_time": 992.307642, "total_time": 1046.668928 }, "output": "https://replicate.delivery/pbxt/4lrw9387HOaKKR7kHv5YX4N59OSP0ltIcfaYWdm2lHAGVCBIA/output.zip", "started_at": "2022-11-20T20:57:37.635118Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/h3wipflhzrexbasf3ngae6em64", "cancel": "https://api.replicate.com/v1/predictions/h3wipflhzrexbasf3ngae6em64/cancel" }, "version": "30afbd7535725ac8f47820b7bc54a72289ad1d08a56dfe13ff77be85ed672888" }
Generated in/root/.pyenv/versions/3.10.8/lib/python3.10/site-packages/accelerate/accelerator.py:179: UserWarning: `log_with=tensorboard` was passed but no supported trackers are currently installed. warnings.warn(f"`log_with={log_with}` was passed but no supported trackers are currently installed.") You have passed `None` for safety_checker to disable its functionality in <class 'diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline'>. Note that this might lead to problems when using <class 'diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline'> and is not recommended. 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2.86it/s, loss=0.279, lr=1e-6] Steps: 100%|█████████▉| 1990/2000 [11:53<00:03, 2.86it/s, loss=0.279, lr=1e-6] Steps: 100%|█████████▉| 1991/2000 [11:53<00:03, 2.86it/s, loss=0.279, lr=1e-6] Steps: 100%|█████████▉| 1992/2000 [11:53<00:02, 2.86it/s, loss=0.279, lr=1e-6] Steps: 100%|█████████▉| 1993/2000 [11:54<00:02, 2.87it/s, loss=0.279, lr=1e-6] Steps: 100%|█████████▉| 1994/2000 [11:54<00:02, 2.88it/s, loss=0.279, lr=1e-6] Steps: 100%|█████████▉| 1995/2000 [11:54<00:01, 2.86it/s, loss=0.279, lr=1e-6] Steps: 100%|█████████▉| 1996/2000 [11:55<00:01, 2.87it/s, loss=0.279, lr=1e-6] Steps: 100%|█████████▉| 1997/2000 [11:55<00:01, 2.88it/s, loss=0.279, lr=1e-6] Steps: 100%|█████████▉| 1998/2000 [11:55<00:00, 2.87it/s, loss=0.279, lr=1e-6] Steps: 100%|█████████▉| 1999/2000 [11:56<00:00, 2.88it/s, loss=0.279, lr=1e-6] Steps: 100%|██████████| 2000/2000 [11:56<00:00, 2.89it/s, loss=0.279, lr=1e-6]You have passed `None` for safety_checker to disable its functionality in <class 'diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline'>. Note that this might lead to problems when using <class 'diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline'> and is not recommended. [*] Weights saved at checkpoints Steps: 100%|██████████| 2000/2000 [12:01<00:00, 2.77it/s, loss=0.279, lr=1e-6] Sun Nov 20 21:13:41 2022 +-----------------------------------------------------------------------------+ | NVIDIA-SMI 510.47.03 Driver Version: 510.47.03 CUDA Version: 11.6 | |-------------------------------+----------------------+----------------------+ | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |===============================+======================+======================| | 0 NVIDIA A100-SXM... Off | 00000000:00:04.0 Off | 0 | | N/A 38C P0 50W / 400W | 2122MiB / 40960MiB | 11% Default | | | | Disabled | +-------------------------------+----------------------+----------------------+ +-----------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=============================================================================| | 0 N/A N/A 343420 C 2119MiB | +-----------------------------------------------------------------------------+ checkpoints/tokenizer checkpoints/unet checkpoints/vae checkpoints/text_encoder checkpoints/feature_extractor checkpoints/args.json checkpoints/model_index.json checkpoints/scheduler checkpoints/tokenizer/vocab.json checkpoints/tokenizer/special_tokens_map.json checkpoints/tokenizer/merges.txt checkpoints/tokenizer/tokenizer_config.json checkpoints/unet/diffusion_pytorch_model.bin checkpoints/unet/config.json checkpoints/vae/diffusion_pytorch_model.bin checkpoints/vae/config.json checkpoints/text_encoder/pytorch_model.bin checkpoints/text_encoder/config.json checkpoints/feature_extractor/preprocessor_config.json checkpoints/scheduler/scheduler_config.json
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