afiaka87/pyglide 🔢📝❓✓ → 🖼️

▶️ 18.6K runs 📅 Jan 2022 ⚙️ Cog 0.4.4 🔗 GitHub 📄 Paper ⚖️ License
text-to-image

About

The predecessor to DALLE-2, GLIDE (filtered) with faster PRK/PLMS sampling.

Example Output

Prompt:

"detailed oil painting of a pembroke welsh corgi"

Output

[object Object]

Performance Metrics

36.10s Prediction Time
36.32s Total Time
All Input Parameters
{
  "seed": 234,
  "prompt": "detailed oil painting of a pembroke welsh corgi",
  "side_x": "64",
  "side_y": "64",
  "batch_size": "3",
  "upsample_temp": "1.0",
  "guidance_scale": 4,
  "upsample_stage": true,
  "timestep_respacing": "35",
  "sr_timestep_respacing": "27"
}
Input Parameters
seed Type: integerDefault: 0
Seed for reproducibility
prompt (required) Type: string
Text prompt to use. Keep it simple/literal and avoid using poetic language (unlike CLIP).
side_x Default: 64
Must be multiple of 8. Going above 64 is not recommended. Actual image will be 4x larger.
side_y Default: 64
Must be multiple of 8. Going above 64 is not recommended. Actual image will be 4x larger.
batch_size Type: integerDefault: 3Range: 1 - 8
Batch size. Number of generations to predict
upsample_temp Default: 0.998
Upsample temperature. Consider lowering to ~0.997 for blurry images with fewer artifacts.
guidance_scale Type: numberDefault: 4
Classifier-free guidance scale. Higher values move further away from unconditional outputs. Lower values move closer to unconditional outputs. Negative values guide towards semantically opposite classes. 4-16 is a reasonable range.
upsample_stage Type: booleanDefault: false
If true, uses both the base and upsample models. If false, only the (finetuned) base model is used. This is useful for testing the upsampler, which is not finetuned.
timestep_respacing Default: 35
Number of timesteps to use for base model PLMS sampling. Usually don't need more than 50.
sr_timestep_respacing Default: 17
Number of timesteps to use for upsample model PLMS sampling. Usually don't need more than 20.
Output Schema

Output

Type: arrayItems Type: stringItems Format: uri

Example Execution Logs
  0%|          | 0/33 [00:00<?, ?it/s]
  3%|▎         | 1/33 [00:00<00:24,  1.31it/s]
  6%|▌         | 2/33 [00:01<00:22,  1.38it/s]
  9%|▉         | 3/33 [00:02<00:21,  1.40it/s]
 12%|█▏        | 4/33 [00:02<00:14,  1.99it/s]
 15%|█▌        | 5/33 [00:02<00:10,  2.59it/s]
 18%|█▊        | 6/33 [00:02<00:08,  3.18it/s]
 21%|██        | 7/33 [00:02<00:07,  3.71it/s]
 24%|██▍       | 8/33 [00:03<00:05,  4.17it/s]
 27%|██▋       | 9/33 [00:03<00:05,  4.54it/s]
 30%|███       | 10/33 [00:03<00:04,  4.82it/s]
 33%|███▎      | 11/33 [00:03<00:04,  5.06it/s]
 36%|███▋      | 12/33 [00:03<00:04,  5.23it/s]
 39%|███▉      | 13/33 [00:03<00:03,  5.36it/s]
 42%|████▏     | 14/33 [00:04<00:03,  5.44it/s]
 45%|████▌     | 15/33 [00:04<00:03,  5.50it/s]
 48%|████▊     | 16/33 [00:04<00:03,  5.54it/s]
 52%|█████▏    | 17/33 [00:04<00:02,  5.56it/s]
 55%|█████▍    | 18/33 [00:04<00:02,  5.59it/s]
 58%|█████▊    | 19/33 [00:04<00:02,  5.60it/s]
 61%|██████    | 20/33 [00:05<00:02,  5.61it/s]
 64%|██████▎   | 21/33 [00:05<00:02,  5.63it/s]
 67%|██████▋   | 22/33 [00:05<00:01,  5.63it/s]
 70%|██████▉   | 23/33 [00:05<00:01,  5.63it/s]
 73%|███████▎  | 24/33 [00:05<00:01,  5.62it/s]
 76%|███████▌  | 25/33 [00:06<00:01,  5.64it/s]
 79%|███████▉  | 26/33 [00:06<00:01,  5.63it/s]
 82%|████████▏ | 27/33 [00:06<00:01,  5.63it/s]
 85%|████████▍ | 28/33 [00:06<00:00,  5.63it/s]
 88%|████████▊ | 29/33 [00:06<00:00,  5.63it/s]
 91%|█████████ | 30/33 [00:06<00:00,  5.63it/s]
 94%|█████████▍| 31/33 [00:07<00:00,  5.62it/s]
 97%|█████████▋| 32/33 [00:07<00:00,  5.63it/s]
100%|██████████| 33/33 [00:07<00:00,  5.62it/s]
100%|██████████| 33/33 [00:07<00:00,  4.41it/s]

  0%|          | 0/25 [00:00<?, ?it/s]
  4%|▍         | 1/25 [00:01<00:45,  1.91s/it]
  8%|▊         | 2/25 [00:03<00:43,  1.91s/it]
 12%|█▏        | 3/25 [00:05<00:42,  1.91s/it]
 16%|█▌        | 4/25 [00:06<00:28,  1.35s/it]
 20%|██        | 5/25 [00:06<00:20,  1.03s/it]
 24%|██▍       | 6/25 [00:07<00:16,  1.18it/s]
 28%|██▊       | 7/25 [00:07<00:13,  1.38it/s]
 32%|███▏      | 8/25 [00:08<00:10,  1.55it/s]
 36%|███▌      | 9/25 [00:08<00:09,  1.69it/s]
 40%|████      | 10/25 [00:09<00:08,  1.79it/s]
 44%|████▍     | 11/25 [00:09<00:07,  1.87it/s]
 48%|████▊     | 12/25 [00:10<00:06,  1.93it/s]
 52%|█████▏    | 13/25 [00:10<00:06,  1.98it/s]
 56%|█████▌    | 14/25 [00:11<00:05,  2.01it/s]
 60%|██████    | 15/25 [00:11<00:04,  2.03it/s]
 64%|██████▍   | 16/25 [00:11<00:04,  2.05it/s]
 68%|██████▊   | 17/25 [00:12<00:03,  2.06it/s]
 72%|███████▏  | 18/25 [00:12<00:03,  2.06it/s]
 76%|███████▌  | 19/25 [00:13<00:02,  2.06it/s]
 80%|████████  | 20/25 [00:13<00:02,  2.07it/s]
 84%|████████▍ | 21/25 [00:14<00:01,  2.07it/s]
 88%|████████▊ | 22/25 [00:14<00:01,  2.07it/s]
 92%|█████████▏| 23/25 [00:15<00:00,  2.07it/s]
 96%|█████████▌| 24/25 [00:15<00:00,  2.07it/s]
100%|██████████| 25/25 [00:16<00:00,  2.07it/s]
100%|██████████| 25/25 [00:16<00:00,  1.53it/s]
Version Details
Version ID
d0b38636cb245fbec3e5a7a26356fa55bc79ea1032f12e5ea821173f171be0b5
Version Created
October 14, 2022
Run on Replicate →