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    "refine": "no_refiner",
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    "total_time": 115.748209
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{
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  "created_at": "2023-11-08T22:30:44.685882Z",
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  "error": null,
  "id": "gnlpln3bgdbmg7kh33d2k3xpcu",
  "input": {
    "seed": 29244,
    "width": 1024,
    "height": 1024,
    "prompt": "A photo of TOK",
    "refine": "no_refiner",
    "lora_url": "https://replicate.delivery/pbxt/N5umn0TVyA4ee0Rjv3WnckjrimvNmMhnYpHcR5eszhzfKvZHB/trained_model.tar",
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  "logs": "LORA\nLoading ssd txt2img pipeline...\nLoading pipeline components...:   0%|          | 0/7 [00:00<?, ?it/s]\nLoading pipeline components...:  29%|██▊       | 2/7 [00:00<00:00, 17.04it/s]\nLoading pipeline components...:  57%|█████▋    | 4/7 [00:00<00:00, 11.74it/s]\nLoading pipeline components...:  86%|████████▌ | 6/7 [00:00<00:00,  6.96it/s]\nLoading pipeline components...: 100%|██████████| 7/7 [00:01<00:00,  5.75it/s]\nLoading pipeline components...: 100%|██████████| 7/7 [00:01<00:00,  6.87it/s]\nLoading ssd lora weights...\nLoading fine-tuned model\nDoes not have Unet. Assume we are using LoRA\nLoading Unet LoRA\nUsing seed: 29244\nPrompt: A photo of <s0><s1>\ntxt2img mode\n  0%|          | 0/50 [00:00<?, ?it/s]\n  2%|▏         | 1/50 [00:00<00:13,  3.67it/s]\n  4%|▍         | 2/50 [00:00<00:10,  4.37it/s]\n  6%|▌         | 3/50 [00:00<00:11,  4.03it/s]\n  8%|▊         | 4/50 [00:01<00:11,  3.89it/s]\n 10%|█         | 5/50 [00:01<00:11,  3.81it/s]\n 12%|█▏        | 6/50 [00:01<00:11,  3.77it/s]\n 14%|█▍        | 7/50 [00:01<00:11,  3.74it/s]\n 16%|█▌        | 8/50 [00:02<00:11,  3.73it/s]\n 18%|█▊        | 9/50 [00:02<00:11,  3.71it/s]\n 20%|██        | 10/50 [00:02<00:10,  3.70it/s]\n 22%|██▏       | 11/50 [00:02<00:10,  3.70it/s]\n 24%|██▍       | 12/50 [00:03<00:10,  3.69it/s]\n 26%|██▌       | 13/50 [00:03<00:10,  3.69it/s]\n 28%|██▊       | 14/50 [00:03<00:09,  3.68it/s]\n 30%|███       | 15/50 [00:04<00:09,  3.68it/s]\n 32%|███▏      | 16/50 [00:04<00:09,  3.68it/s]\n 34%|███▍      | 17/50 [00:04<00:08,  3.68it/s]\n 36%|███▌      | 18/50 [00:04<00:08,  3.68it/s]\n 38%|███▊      | 19/50 [00:05<00:08,  3.68it/s]\n 40%|████      | 20/50 [00:05<00:08,  3.67it/s]\n 42%|████▏     | 21/50 [00:05<00:07,  3.68it/s]\n 44%|████▍     | 22/50 [00:05<00:07,  3.67it/s]\n 46%|████▌     | 23/50 [00:06<00:07,  3.67it/s]\n 48%|████▊     | 24/50 [00:06<00:07,  3.67it/s]\n 50%|█████     | 25/50 [00:06<00:06,  3.67it/s]\n 52%|█████▏    | 26/50 [00:06<00:06,  3.67it/s]\n 54%|█████▍    | 27/50 [00:07<00:06,  3.67it/s]\n 56%|█████▌    | 28/50 [00:07<00:05,  3.67it/s]\n 58%|█████▊    | 29/50 [00:07<00:05,  3.67it/s]\n 60%|██████    | 30/50 [00:08<00:05,  3.67it/s]\n 62%|██████▏   | 31/50 [00:08<00:05,  3.67it/s]\n 64%|██████▍   | 32/50 [00:08<00:04,  3.67it/s]\n 66%|██████▌   | 33/50 [00:08<00:04,  3.67it/s]\n 68%|██████▊   | 34/50 [00:09<00:04,  3.67it/s]\n 70%|███████   | 35/50 [00:09<00:04,  3.67it/s]\n 72%|███████▏  | 36/50 [00:09<00:03,  3.67it/s]\n 74%|███████▍  | 37/50 [00:09<00:03,  3.67it/s]\n 76%|███████▌  | 38/50 [00:10<00:03,  3.67it/s]\n 78%|███████▊  | 39/50 [00:10<00:03,  3.67it/s]\n 80%|████████  | 40/50 [00:10<00:02,  3.67it/s]\n 82%|████████▏ | 41/50 [00:11<00:02,  3.67it/s]\n 84%|████████▍ | 42/50 [00:11<00:02,  3.66it/s]\n 86%|████████▌ | 43/50 [00:11<00:01,  3.66it/s]\n 88%|████████▊ | 44/50 [00:11<00:01,  3.66it/s]\n 90%|█████████ | 45/50 [00:12<00:01,  3.67it/s]\n 92%|█████████▏| 46/50 [00:12<00:01,  3.67it/s]\n 94%|█████████▍| 47/50 [00:12<00:00,  3.68it/s]\n 96%|█████████▌| 48/50 [00:12<00:00,  3.68it/s]\n 98%|█████████▊| 49/50 [00:13<00:00,  3.69it/s]\n100%|██████████| 50/50 [00:13<00:00,  3.69it/s]\n100%|██████████| 50/50 [00:13<00:00,  3.69it/s]",
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