prunaai / vace-14b
This is a faster VACE-14B model, optimised with pruna, contact us for more at pruna.ai
Prediction
prunaai/vace-14b:deea42022431a57b75ae58af3c26cfaa9adf006b9c67d0b19a64a8f5ab55de03Input
- seed
- -1
- size
- 832*480
- prompt
- An apple being cut by a knife
- frame_num
- 81
- speed_mode
- Lightly Juiced 🍊 (more consistent)
- sample_shift
- 16
- sample_steps
- 50
- sample_solver
- unipc
- sample_guide_scale
- 5
{ "seed": -1, "size": "832*480", "prompt": "An apple being cut by a knife", "frame_num": 81, "speed_mode": "Lightly Juiced 🍊 (more consistent)", "sample_shift": 16, "sample_steps": 50, "sample_solver": "unipc", "sample_guide_scale": 5 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run prunaai/vace-14b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "prunaai/vace-14b:deea42022431a57b75ae58af3c26cfaa9adf006b9c67d0b19a64a8f5ab55de03", { input: { seed: -1, size: "832*480", prompt: "An apple being cut by a knife", frame_num: 81, speed_mode: "Lightly Juiced 🍊 (more consistent)", sample_shift: 16, sample_steps: 50, sample_solver: "unipc", sample_guide_scale: 5 } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", 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 prunaai/vace-14b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "prunaai/vace-14b:deea42022431a57b75ae58af3c26cfaa9adf006b9c67d0b19a64a8f5ab55de03", input={ "seed": -1, "size": "832*480", "prompt": "An apple being cut by a knife", "frame_num": 81, "speed_mode": "Lightly Juiced 🍊 (more consistent)", "sample_shift": 16, "sample_steps": 50, "sample_solver": "unipc", "sample_guide_scale": 5 } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())To learn more, take a look at the guide on getting started with Python.
Run prunaai/vace-14b 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": "prunaai/vace-14b:deea42022431a57b75ae58af3c26cfaa9adf006b9c67d0b19a64a8f5ab55de03", "input": { "seed": -1, "size": "832*480", "prompt": "An apple being cut by a knife", "frame_num": 81, "speed_mode": "Lightly Juiced 🍊 (more consistent)", "sample_shift": 16, "sample_steps": 50, "sample_solver": "unipc", "sample_guide_scale": 5 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-05-16T14:59:41.034471Z", "created_at": "2025-05-16T14:51:05.336000Z", "data_removed": false, "error": null, "id": "3gpdam6gz1rma0cpv69vdqjxx8", "input": { "seed": -1, "size": "832*480", "prompt": "An apple being cut by a knife", "frame_num": 81, "speed_mode": "Lightly Juiced 🍊 (more consistent)", "sample_shift": 16, "sample_steps": 50, "sample_solver": "unipc", "sample_guide_scale": 5 }, "logs": "0%| | 0/50 [00:00<?, ?it/s]W0516 14:51:55.512000 167 site-packages/torch/fx/experimental/symbolic_shapes.py:6307] [0/0] failed during evaluate_expr(Eq(32760, u0*u1*u2), hint=None, size_oblivious=True, forcing_spec=False\nE0516 14:51:55.512000 167 site-packages/torch/fx/experimental/recording.py:299] [0/0] failed while running evaluate_expr(*(Eq(32760, u0*u1*u2), None), **{'fx_node': False, 'size_oblivious': True})\nW0516 14:51:57.095000 167 site-packages/torch/fx/experimental/symbolic_shapes.py:6307] [1/0] failed during evaluate_expr(Eq(32760, u0*u1*u2), hint=None, size_oblivious=True, forcing_spec=False\nE0516 14:51:57.095000 167 site-packages/torch/fx/experimental/recording.py:299] [1/0] failed while running evaluate_expr(*(Eq(32760, u0*u1*u2), None), **{'fx_node': False, 'size_oblivious': True})\nW0516 14:51:57.627000 167 site-packages/torch/fx/experimental/symbolic_shapes.py:6307] [2/0] failed during evaluate_expr(Eq(32760, u0*u1*u2), hint=None, size_oblivious=True, forcing_spec=False\nE0516 14:51:57.627000 167 site-packages/torch/fx/experimental/recording.py:299] [2/0] failed while running evaluate_expr(*(Eq(32760, u0*u1*u2), None), **{'fx_node': False, 'size_oblivious': True})\nW0516 14:51:58.928000 167 site-packages/torch/fx/experimental/symbolic_shapes.py:6307] [3/0] failed during evaluate_expr(Eq(32760, u0*u1*u2), hint=None, size_oblivious=True, forcing_spec=False\nE0516 14:51:58.928000 167 site-packages/torch/fx/experimental/recording.py:299] [3/0] failed while running evaluate_expr(*(Eq(32760, u0*u1*u2), None), **{'fx_node': False, 'size_oblivious': True})\nW0516 14:51:58.946000 167 site-packages/torch/fx/experimental/symbolic_shapes.py:6307] [4/0] failed during evaluate_expr(Eq(32760, u0*u1*u2), hint=None, size_oblivious=True, forcing_spec=False\nE0516 14:51:58.946000 167 site-packages/torch/fx/experimental/recording.py:299] [4/0] failed while running evaluate_expr(*(Eq(32760, u0*u1*u2), None), **{'fx_node': False, 'size_oblivious': True})\nW0516 14:52:11.442000 167 site-packages/torch/fx/experimental/symbolic_shapes.py:6307] [0/1] failed during evaluate_expr(Eq(32760, u0*u1*u2), hint=None, size_oblivious=True, forcing_spec=False\nE0516 14:52:11.442000 167 site-packages/torch/fx/experimental/recording.py:299] [0/1] failed while running evaluate_expr(*(Eq(32760, u0*u1*u2), None), **{'fx_node': False, 'size_oblivious': True})\nW0516 14:52:11.508000 167 site-packages/torch/fx/experimental/symbolic_shapes.py:6307] [1/1] failed during evaluate_expr(Eq(32760, u0*u1*u2), hint=None, size_oblivious=True, forcing_spec=False\nE0516 14:52:11.509000 167 site-packages/torch/fx/experimental/recording.py:299] [1/1] failed while running evaluate_expr(*(Eq(32760, u0*u1*u2), None), **{'fx_node': False, 'size_oblivious': True})\nW0516 14:52:13.232000 167 site-packages/torch/fx/experimental/symbolic_shapes.py:6307] [12/0] failed during evaluate_expr(Eq(32760, u0*u1*u2), hint=None, size_oblivious=True, forcing_spec=False\nE0516 14:52:13.232000 167 site-packages/torch/fx/experimental/recording.py:299] [12/0] failed while running evaluate_expr(*(Eq(32760, u0*u1*u2), None), **{'fx_node': False, 'size_oblivious': True})\nW0516 14:52:13.290000 167 site-packages/torch/fx/experimental/symbolic_shapes.py:6307] [1/2] failed during evaluate_expr(Eq(32760, u0*u1*u2), hint=None, size_oblivious=True, forcing_spec=False\nE0516 14:52:13.291000 167 site-packages/torch/fx/experimental/recording.py:299] [1/2] failed while running evaluate_expr(*(Eq(32760, u0*u1*u2), None), **{'fx_node': False, 'size_oblivious': True})\nW0516 14:52:14.826000 167 site-packages/torch/fx/experimental/symbolic_shapes.py:6307] [12/1] failed during evaluate_expr(Eq(32760, u0*u1*u2), hint=None, size_oblivious=True, forcing_spec=False\nE0516 14:52:14.826000 167 site-packages/torch/fx/experimental/recording.py:299] [12/1] failed while running evaluate_expr(*(Eq(32760, u0*u1*u2), None), **{'fx_node': False, 'size_oblivious': True})\nW0516 14:52:14.883000 167 site-packages/torch/fx/experimental/symbolic_shapes.py:6307] [1/3] failed during evaluate_expr(Eq(32760, u0*u1*u2), hint=None, size_oblivious=True, forcing_spec=False\nE0516 14:52:14.883000 167 site-packages/torch/fx/experimental/recording.py:299] [1/3] failed while running evaluate_expr(*(Eq(32760, u0*u1*u2), None), **{'fx_node': False, 'size_oblivious': True})\n 2%|▏ | 1/50 [00:29<23:49, 29.18s/it]\n 4%|▍ | 2/50 [00:39<14:18, 17.89s/it]\n 6%|▌ | 3/50 [00:49<11:12, 14.30s/it]\n 8%|▊ | 4/50 [00:59<09:40, 12.61s/it]\n 10%|█ | 5/50 [01:09<08:45, 11.68s/it]\n 12%|█▏ | 6/50 [01:19<08:09, 11.13s/it]\n 14%|█▍ | 7/50 [01:29<07:43, 10.77s/it]\n 16%|█▌ | 8/50 [01:39<07:22, 10.54s/it]\n 18%|█▊ | 9/50 [01:49<07:05, 10.39s/it]\n 20%|██ | 10/50 [01:59<06:51, 10.28s/it]\n 22%|██▏ | 11/50 [02:09<06:38, 10.21s/it]\n 24%|██▍ | 12/50 [02:19<06:26, 10.17s/it]\n 26%|██▌ | 13/50 [02:29<06:15, 10.15s/it]\n 28%|██▊ | 14/50 [02:39<06:04, 10.13s/it]\n 30%|███ | 15/50 [02:49<05:53, 10.11s/it]\n 32%|███▏ | 16/50 [02:59<05:43, 10.10s/it]\n 34%|███▍ | 17/50 [03:09<05:32, 10.07s/it]\n 36%|███▌ | 18/50 [03:19<05:21, 10.05s/it]\n 38%|███▊ | 19/50 [03:29<05:11, 10.04s/it]\n 40%|████ | 20/50 [03:39<05:00, 10.03s/it]\n 42%|████▏ | 21/50 [03:49<04:50, 10.02s/it]\n 44%|████▍ | 22/50 [03:59<04:40, 10.01s/it]\n 48%|████▊ | 24/50 [04:09<03:20, 7.70s/it]\n 52%|█████▏ | 26/50 [04:20<02:39, 6.63s/it]\n 56%|█████▌ | 28/50 [04:30<02:13, 6.05s/it]\n 60%|██████ | 30/50 [04:40<01:53, 5.69s/it]\n 62%|██████▏ | 31/50 [04:50<02:04, 6.54s/it]\n 66%|██████▌ | 33/50 [05:00<01:41, 5.99s/it]\n 68%|██████▊ | 34/50 [05:10<01:48, 6.81s/it]\n 72%|███████▏ | 36/50 [05:20<01:26, 6.15s/it]\n 76%|███████▌ | 38/50 [05:30<01:09, 5.75s/it]\n 80%|████████ | 40/50 [05:40<00:55, 5.51s/it]\n 84%|████████▍ | 42/50 [05:50<00:42, 5.35s/it]\n 88%|████████▊ | 44/50 [06:00<00:31, 5.24s/it]\n 90%|█████████ | 45/50 [06:10<00:30, 6.11s/it]\n 92%|█████████▏| 46/50 [06:20<00:27, 6.92s/it]\n 94%|█████████▍| 47/50 [06:30<00:22, 7.63s/it]\n 96%|█████████▌| 48/50 [06:40<00:16, 8.21s/it]\n 98%|█████████▊| 49/50 [06:50<00:08, 8.67s/it]\n100%|██████████| 50/50 [07:00<00:00, 9.03s/it]\n100%|██████████| 50/50 [07:00<00:00, 8.40s/it]", "metrics": { "predict_time": 475.508270468, "total_time": 515.698471 }, "output": "https://replicate.delivery/xezq/IKSvf6HkSXwIXKkf7la36IGefzsK5Z6abxzpnuDgtedvbCqlC/output.mp4", "started_at": "2025-05-16T14:51:45.526201Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-td6llf6kllgvdiaflgc7bmw6skoal4nk7r2vxvuzc2zaydl6y44a", "get": "https://api.replicate.com/v1/predictions/3gpdam6gz1rma0cpv69vdqjxx8", "cancel": "https://api.replicate.com/v1/predictions/3gpdam6gz1rma0cpv69vdqjxx8/cancel" }, "version": "deea42022431a57b75ae58af3c26cfaa9adf006b9c67d0b19a64a8f5ab55de03" }Generated in0%| | 0/50 [00:00<?, ?it/s]W0516 14:51:55.512000 167 site-packages/torch/fx/experimental/symbolic_shapes.py:6307] [0/0] failed during evaluate_expr(Eq(32760, u0*u1*u2), hint=None, size_oblivious=True, forcing_spec=False E0516 14:51:55.512000 167 site-packages/torch/fx/experimental/recording.py:299] [0/0] failed while running evaluate_expr(*(Eq(32760, u0*u1*u2), None), **{'fx_node': False, 'size_oblivious': True}) W0516 14:51:57.095000 167 site-packages/torch/fx/experimental/symbolic_shapes.py:6307] [1/0] failed during evaluate_expr(Eq(32760, u0*u1*u2), hint=None, size_oblivious=True, forcing_spec=False E0516 14:51:57.095000 167 site-packages/torch/fx/experimental/recording.py:299] [1/0] failed while running evaluate_expr(*(Eq(32760, u0*u1*u2), None), **{'fx_node': False, 'size_oblivious': True}) W0516 14:51:57.627000 167 site-packages/torch/fx/experimental/symbolic_shapes.py:6307] [2/0] failed during evaluate_expr(Eq(32760, u0*u1*u2), hint=None, size_oblivious=True, forcing_spec=False E0516 14:51:57.627000 167 site-packages/torch/fx/experimental/recording.py:299] [2/0] failed while running evaluate_expr(*(Eq(32760, u0*u1*u2), None), **{'fx_node': False, 'size_oblivious': True}) W0516 14:51:58.928000 167 site-packages/torch/fx/experimental/symbolic_shapes.py:6307] [3/0] failed during evaluate_expr(Eq(32760, u0*u1*u2), hint=None, size_oblivious=True, forcing_spec=False E0516 14:51:58.928000 167 site-packages/torch/fx/experimental/recording.py:299] [3/0] failed while running evaluate_expr(*(Eq(32760, u0*u1*u2), None), **{'fx_node': False, 'size_oblivious': True}) W0516 14:51:58.946000 167 site-packages/torch/fx/experimental/symbolic_shapes.py:6307] [4/0] failed during evaluate_expr(Eq(32760, u0*u1*u2), hint=None, size_oblivious=True, forcing_spec=False E0516 14:51:58.946000 167 site-packages/torch/fx/experimental/recording.py:299] [4/0] failed while running evaluate_expr(*(Eq(32760, u0*u1*u2), None), **{'fx_node': False, 'size_oblivious': True}) W0516 14:52:11.442000 167 site-packages/torch/fx/experimental/symbolic_shapes.py:6307] [0/1] failed during evaluate_expr(Eq(32760, u0*u1*u2), hint=None, size_oblivious=True, forcing_spec=False E0516 14:52:11.442000 167 site-packages/torch/fx/experimental/recording.py:299] [0/1] failed while running evaluate_expr(*(Eq(32760, u0*u1*u2), None), **{'fx_node': False, 'size_oblivious': True}) W0516 14:52:11.508000 167 site-packages/torch/fx/experimental/symbolic_shapes.py:6307] [1/1] failed during evaluate_expr(Eq(32760, u0*u1*u2), hint=None, size_oblivious=True, forcing_spec=False E0516 14:52:11.509000 167 site-packages/torch/fx/experimental/recording.py:299] [1/1] failed while running evaluate_expr(*(Eq(32760, u0*u1*u2), None), **{'fx_node': False, 'size_oblivious': True}) W0516 14:52:13.232000 167 site-packages/torch/fx/experimental/symbolic_shapes.py:6307] [12/0] failed during evaluate_expr(Eq(32760, u0*u1*u2), hint=None, size_oblivious=True, forcing_spec=False E0516 14:52:13.232000 167 site-packages/torch/fx/experimental/recording.py:299] [12/0] failed while running evaluate_expr(*(Eq(32760, u0*u1*u2), None), **{'fx_node': False, 'size_oblivious': True}) W0516 14:52:13.290000 167 site-packages/torch/fx/experimental/symbolic_shapes.py:6307] [1/2] failed during evaluate_expr(Eq(32760, u0*u1*u2), hint=None, size_oblivious=True, forcing_spec=False E0516 14:52:13.291000 167 site-packages/torch/fx/experimental/recording.py:299] [1/2] failed while running evaluate_expr(*(Eq(32760, u0*u1*u2), None), **{'fx_node': False, 'size_oblivious': True}) W0516 14:52:14.826000 167 site-packages/torch/fx/experimental/symbolic_shapes.py:6307] [12/1] failed during evaluate_expr(Eq(32760, u0*u1*u2), hint=None, size_oblivious=True, forcing_spec=False E0516 14:52:14.826000 167 site-packages/torch/fx/experimental/recording.py:299] [12/1] failed while running evaluate_expr(*(Eq(32760, u0*u1*u2), None), **{'fx_node': False, 'size_oblivious': True}) W0516 14:52:14.883000 167 site-packages/torch/fx/experimental/symbolic_shapes.py:6307] [1/3] failed during evaluate_expr(Eq(32760, u0*u1*u2), hint=None, size_oblivious=True, forcing_spec=False E0516 14:52:14.883000 167 site-packages/torch/fx/experimental/recording.py:299] [1/3] failed while running evaluate_expr(*(Eq(32760, u0*u1*u2), None), **{'fx_node': False, 'size_oblivious': True}) 2%|▏ | 1/50 [00:29<23:49, 29.18s/it] 4%|▍ | 2/50 [00:39<14:18, 17.89s/it] 6%|▌ | 3/50 [00:49<11:12, 14.30s/it] 8%|▊ | 4/50 [00:59<09:40, 12.61s/it] 10%|█ | 5/50 [01:09<08:45, 11.68s/it] 12%|█▏ | 6/50 [01:19<08:09, 11.13s/it] 14%|█▍ | 7/50 [01:29<07:43, 10.77s/it] 16%|█▌ | 8/50 [01:39<07:22, 10.54s/it] 18%|█▊ | 9/50 [01:49<07:05, 10.39s/it] 20%|██ | 10/50 [01:59<06:51, 10.28s/it] 22%|██▏ | 11/50 [02:09<06:38, 10.21s/it] 24%|██▍ | 12/50 [02:19<06:26, 10.17s/it] 26%|██▌ | 13/50 [02:29<06:15, 10.15s/it] 28%|██▊ | 14/50 [02:39<06:04, 10.13s/it] 30%|███ | 15/50 [02:49<05:53, 10.11s/it] 32%|███▏ | 16/50 [02:59<05:43, 10.10s/it] 34%|███▍ | 17/50 [03:09<05:32, 10.07s/it] 36%|███▌ | 18/50 [03:19<05:21, 10.05s/it] 38%|███▊ | 19/50 [03:29<05:11, 10.04s/it] 40%|████ | 20/50 [03:39<05:00, 10.03s/it] 42%|████▏ | 21/50 [03:49<04:50, 10.02s/it] 44%|████▍ | 22/50 [03:59<04:40, 10.01s/it] 48%|████▊ | 24/50 [04:09<03:20, 7.70s/it] 52%|█████▏ | 26/50 [04:20<02:39, 6.63s/it] 56%|█████▌ | 28/50 [04:30<02:13, 6.05s/it] 60%|██████ | 30/50 [04:40<01:53, 5.69s/it] 62%|██████▏ | 31/50 [04:50<02:04, 6.54s/it] 66%|██████▌ | 33/50 [05:00<01:41, 5.99s/it] 68%|██████▊ | 34/50 [05:10<01:48, 6.81s/it] 72%|███████▏ | 36/50 [05:20<01:26, 6.15s/it] 76%|███████▌ | 38/50 [05:30<01:09, 5.75s/it] 80%|████████ | 40/50 [05:40<00:55, 5.51s/it] 84%|████████▍ | 42/50 [05:50<00:42, 5.35s/it] 88%|████████▊ | 44/50 [06:00<00:31, 5.24s/it] 90%|█████████ | 45/50 [06:10<00:30, 6.11s/it] 92%|█████████▏| 46/50 [06:20<00:27, 6.92s/it] 94%|█████████▍| 47/50 [06:30<00:22, 7.63s/it] 96%|█████████▌| 48/50 [06:40<00:16, 8.21s/it] 98%|█████████▊| 49/50 [06:50<00:08, 8.67s/it] 100%|██████████| 50/50 [07:00<00:00, 9.03s/it] 100%|██████████| 50/50 [07:00<00:00, 8.40s/it]Prediction
prunaai/vace-14b:deea42022431a57b75ae58af3c26cfaa9adf006b9c67d0b19a64a8f5ab55de03IDzf7pxmpgnnrma0cpv90s6jct3mStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- seed
- -1
- size
- 832*480
- prompt
- "In a joyful and festive scene, a little girl wearing a bright red spring outfit is playing with her cute cartoon snake. Her outfit is embroidered with golden auspicious patterns, radiating a festive atmosphere, and her face is beaming with a bright smile. The snake has a vibrant green body with a rounded shape and large eyes that make it look both friendly and humorous. The little girl happily strokes the snake's head gently, sharing this warm moment together. Colorful lanterns and ribbons decorate the surroundings, with sunlight shining upon them, creating an atmosphere full of friendship and happiness for the New Year.
- frame_num
- 81
- speed_mode
- Extra Juiced 🚀 (even more speed)
- sample_shift
- 16
- sample_steps
- 50
- sample_solver
- unipc
- src_ref_images
- sample_guide_scale
- 5
{ "seed": -1, "size": "832*480", "prompt": "\"In a joyful and festive scene, a little girl wearing a bright red spring outfit is playing with her cute cartoon snake. Her outfit is embroidered with golden auspicious patterns, radiating a festive atmosphere, and her face is beaming with a bright smile. The snake has a vibrant green body with a rounded shape and large eyes that make it look both friendly and humorous. The little girl happily strokes the snake's head gently, sharing this warm moment together. Colorful lanterns and ribbons decorate the surroundings, with sunlight shining upon them, creating an atmosphere full of friendship and happiness for the New Year.", "frame_num": 81, "speed_mode": "Extra Juiced 🚀 (even more speed)", "sample_shift": 16, "sample_steps": 50, "sample_solver": "unipc", "src_ref_images": [ "https://replicate.delivery/pbxt/N1IM7L1cOTAHdcJCoMGkoXlvy4fwb06TuVo2w85Nvdq2Ces4/girl.png", "https://replicate.delivery/pbxt/N1IM7PacBe0R9mFt0rIk5rmZpOOlw99OWGQxntNH5aZjvser/snake.png" ], "sample_guide_scale": 5 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run prunaai/vace-14b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "prunaai/vace-14b:deea42022431a57b75ae58af3c26cfaa9adf006b9c67d0b19a64a8f5ab55de03", { input: { seed: -1, size: "832*480", prompt: "\"In a joyful and festive scene, a little girl wearing a bright red spring outfit is playing with her cute cartoon snake. Her outfit is embroidered with golden auspicious patterns, radiating a festive atmosphere, and her face is beaming with a bright smile. The snake has a vibrant green body with a rounded shape and large eyes that make it look both friendly and humorous. The little girl happily strokes the snake's head gently, sharing this warm moment together. Colorful lanterns and ribbons decorate the surroundings, with sunlight shining upon them, creating an atmosphere full of friendship and happiness for the New Year.", frame_num: 81, speed_mode: "Extra Juiced 🚀 (even more speed)", sample_shift: 16, sample_steps: 50, sample_solver: "unipc", src_ref_images: ["https://replicate.delivery/pbxt/N1IM7L1cOTAHdcJCoMGkoXlvy4fwb06TuVo2w85Nvdq2Ces4/girl.png","https://replicate.delivery/pbxt/N1IM7PacBe0R9mFt0rIk5rmZpOOlw99OWGQxntNH5aZjvser/snake.png"], sample_guide_scale: 5 } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", 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 prunaai/vace-14b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "prunaai/vace-14b:deea42022431a57b75ae58af3c26cfaa9adf006b9c67d0b19a64a8f5ab55de03", input={ "seed": -1, "size": "832*480", "prompt": "\"In a joyful and festive scene, a little girl wearing a bright red spring outfit is playing with her cute cartoon snake. Her outfit is embroidered with golden auspicious patterns, radiating a festive atmosphere, and her face is beaming with a bright smile. The snake has a vibrant green body with a rounded shape and large eyes that make it look both friendly and humorous. The little girl happily strokes the snake's head gently, sharing this warm moment together. Colorful lanterns and ribbons decorate the surroundings, with sunlight shining upon them, creating an atmosphere full of friendship and happiness for the New Year.", "frame_num": 81, "speed_mode": "Extra Juiced 🚀 (even more speed)", "sample_shift": 16, "sample_steps": 50, "sample_solver": "unipc", "src_ref_images": ["https://replicate.delivery/pbxt/N1IM7L1cOTAHdcJCoMGkoXlvy4fwb06TuVo2w85Nvdq2Ces4/girl.png","https://replicate.delivery/pbxt/N1IM7PacBe0R9mFt0rIk5rmZpOOlw99OWGQxntNH5aZjvser/snake.png"], "sample_guide_scale": 5 } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())To learn more, take a look at the guide on getting started with Python.
Run prunaai/vace-14b 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": "prunaai/vace-14b:deea42022431a57b75ae58af3c26cfaa9adf006b9c67d0b19a64a8f5ab55de03", "input": { "seed": -1, "size": "832*480", "prompt": "\\"In a joyful and festive scene, a little girl wearing a bright red spring outfit is playing with her cute cartoon snake. Her outfit is embroidered with golden auspicious patterns, radiating a festive atmosphere, and her face is beaming with a bright smile. The snake has a vibrant green body with a rounded shape and large eyes that make it look both friendly and humorous. The little girl happily strokes the snake\'s head gently, sharing this warm moment together. Colorful lanterns and ribbons decorate the surroundings, with sunlight shining upon them, creating an atmosphere full of friendship and happiness for the New Year.", "frame_num": 81, "speed_mode": "Extra Juiced 🚀 (even more speed)", "sample_shift": 16, "sample_steps": 50, "sample_solver": "unipc", "src_ref_images": ["https://replicate.delivery/pbxt/N1IM7L1cOTAHdcJCoMGkoXlvy4fwb06TuVo2w85Nvdq2Ces4/girl.png","https://replicate.delivery/pbxt/N1IM7PacBe0R9mFt0rIk5rmZpOOlw99OWGQxntNH5aZjvser/snake.png"], "sample_guide_scale": 5 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-05-16T18:05:53.086421Z", "created_at": "2025-05-16T18:01:08.525000Z", "data_removed": false, "error": null, "id": "zf7pxmpgnnrma0cpv90s6jct3m", "input": { "seed": -1, "size": "832*480", "prompt": "\"In a joyful and festive scene, a little girl wearing a bright red spring outfit is playing with her cute cartoon snake. Her outfit is embroidered with golden auspicious patterns, radiating a festive atmosphere, and her face is beaming with a bright smile. The snake has a vibrant green body with a rounded shape and large eyes that make it look both friendly and humorous. The little girl happily strokes the snake's head gently, sharing this warm moment together. Colorful lanterns and ribbons decorate the surroundings, with sunlight shining upon them, creating an atmosphere full of friendship and happiness for the New Year.", "frame_num": 81, "speed_mode": "Extra Juiced 🚀 (even more speed)", "sample_shift": 16, "sample_steps": 50, "sample_solver": "unipc", "src_ref_images": [ "https://replicate.delivery/pbxt/N1IM7L1cOTAHdcJCoMGkoXlvy4fwb06TuVo2w85Nvdq2Ces4/girl.png", "https://replicate.delivery/pbxt/N1IM7PacBe0R9mFt0rIk5rmZpOOlw99OWGQxntNH5aZjvser/snake.png" ], "sample_guide_scale": 5 }, "logs": "0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:11<09:36, 11.76s/it]\n 4%|▍ | 2/50 [00:23<09:25, 11.77s/it]\n 6%|▌ | 3/50 [00:35<09:14, 11.79s/it]\n 8%|▊ | 4/50 [00:47<09:02, 11.80s/it]\n 10%|█ | 5/50 [00:59<08:51, 11.81s/it]\n 12%|█▏ | 6/50 [01:10<08:39, 11.81s/it]\n 14%|█▍ | 7/50 [01:22<08:28, 11.81s/it]\n 18%|█▊ | 9/50 [01:34<06:08, 8.98s/it]\n 22%|██▏ | 11/50 [01:46<05:01, 7.72s/it]\n 26%|██▌ | 13/50 [01:58<04:21, 7.06s/it]\n 30%|███ | 15/50 [01:58<02:42, 4.65s/it]\n 34%|███▍ | 17/50 [02:10<02:47, 5.08s/it]\n 42%|████▏ | 21/50 [02:21<01:57, 4.04s/it]\n 48%|████▊ | 24/50 [02:33<01:44, 4.01s/it]\n 56%|█████▌ | 28/50 [02:45<01:18, 3.59s/it]\n 68%|██████▊ | 34/50 [02:57<00:45, 2.85s/it]\n 76%|███████▌ | 38/50 [03:09<00:34, 2.88s/it]\n 84%|████████▍ | 42/50 [03:20<00:23, 2.90s/it]\n 92%|█████████▏| 46/50 [03:32<00:11, 2.91s/it]\n 96%|█████████▌| 48/50 [03:44<00:06, 3.44s/it]\n 98%|█████████▊| 49/50 [03:56<00:04, 4.37s/it]\n100%|██████████| 50/50 [03:56<00:00, 4.73s/it]", "metrics": { "predict_time": 284.550547507, "total_time": 284.561421 }, "output": "https://replicate.delivery/xezq/f1yF5elgtgpX9UaR089xrfUU03ibM2pn1A9MVaGo3CsCEmapA/output.mp4", "started_at": "2025-05-16T18:01:08.535874Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-krvpsbhsxwwh7acwhvor4geulnmye3becsikl6p5bfwx2cqs33wq", "get": "https://api.replicate.com/v1/predictions/zf7pxmpgnnrma0cpv90s6jct3m", "cancel": "https://api.replicate.com/v1/predictions/zf7pxmpgnnrma0cpv90s6jct3m/cancel" }, "version": "deea42022431a57b75ae58af3c26cfaa9adf006b9c67d0b19a64a8f5ab55de03" }Generated in0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:11<09:36, 11.76s/it] 4%|▍ | 2/50 [00:23<09:25, 11.77s/it] 6%|▌ | 3/50 [00:35<09:14, 11.79s/it] 8%|▊ | 4/50 [00:47<09:02, 11.80s/it] 10%|█ | 5/50 [00:59<08:51, 11.81s/it] 12%|█▏ | 6/50 [01:10<08:39, 11.81s/it] 14%|█▍ | 7/50 [01:22<08:28, 11.81s/it] 18%|█▊ | 9/50 [01:34<06:08, 8.98s/it] 22%|██▏ | 11/50 [01:46<05:01, 7.72s/it] 26%|██▌ | 13/50 [01:58<04:21, 7.06s/it] 30%|███ | 15/50 [01:58<02:42, 4.65s/it] 34%|███▍ | 17/50 [02:10<02:47, 5.08s/it] 42%|████▏ | 21/50 [02:21<01:57, 4.04s/it] 48%|████▊ | 24/50 [02:33<01:44, 4.01s/it] 56%|█████▌ | 28/50 [02:45<01:18, 3.59s/it] 68%|██████▊ | 34/50 [02:57<00:45, 2.85s/it] 76%|███████▌ | 38/50 [03:09<00:34, 2.88s/it] 84%|████████▍ | 42/50 [03:20<00:23, 2.90s/it] 92%|█████████▏| 46/50 [03:32<00:11, 2.91s/it] 96%|█████████▌| 48/50 [03:44<00:06, 3.44s/it] 98%|█████████▊| 49/50 [03:56<00:04, 4.37s/it] 100%|██████████| 50/50 [03:56<00:00, 4.73s/it]Prediction
prunaai/vace-14b:bbafc615de3e3903470a335f94294810ced166309adcba307ac8692113a7b273Input
- seed
- -1
- size
- 1280*720
- prompt
- The video shows a man riding a horse on a vast grassland. He has long lavender hair and wears a traditional dress of a white top and black pants. The animation style makes him look like he is doing some kind of outdoor activity or performing. The background is a spectacular mountain range and cloud sky, giving a sense of tranquility and vastness. The entire video is shot from a fixed angle, focusing on the rider and his horse.
- src_mask
- frame_num
- 81
- src_video
- speed_mode
- Extra Juiced 🚀 (even more speed)
- sample_shift
- 16
- sample_steps
- 50
- sample_solver
- unipc
- src_ref_images
- sample_guide_scale
- 5
{ "seed": -1, "size": "1280*720", "prompt": "The video shows a man riding a horse on a vast grassland. He has long lavender hair and wears a traditional dress of a white top and black pants. The animation style makes him look like he is doing some kind of outdoor activity or performing. The background is a spectacular mountain range and cloud sky, giving a sense of tranquility and vastness. The entire video is shot from a fixed angle, focusing on the rider and his horse.", "src_mask": "https://replicate.delivery/pbxt/N323tegI7AuoZmg0U5CuTKa7VBFC4gymhe0kT8Jk3o2sjUUj/src_mask.mp4", "frame_num": 81, "src_video": "https://replicate.delivery/pbxt/N323u1ljtNYyyaLrgw0ZLmXgepvWlBvxbJWi3sAa2VDPuNus/src_video.mp4", "speed_mode": "Extra Juiced 🚀 (even more speed)", "sample_shift": 16, "sample_steps": 50, "sample_solver": "unipc", "src_ref_images": [ "https://replicate.delivery/pbxt/N323t5X69JB1MPD4w4cDIxK4rm0BG0W2JOWBrDrR4O9HTcyp/src_ref_image_1.png" ], "sample_guide_scale": 5 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run prunaai/vace-14b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "prunaai/vace-14b:bbafc615de3e3903470a335f94294810ced166309adcba307ac8692113a7b273", { input: { seed: -1, size: "1280*720", prompt: "The video shows a man riding a horse on a vast grassland. He has long lavender hair and wears a traditional dress of a white top and black pants. The animation style makes him look like he is doing some kind of outdoor activity or performing. The background is a spectacular mountain range and cloud sky, giving a sense of tranquility and vastness. The entire video is shot from a fixed angle, focusing on the rider and his horse.", src_mask: "https://replicate.delivery/pbxt/N323tegI7AuoZmg0U5CuTKa7VBFC4gymhe0kT8Jk3o2sjUUj/src_mask.mp4", frame_num: 81, src_video: "https://replicate.delivery/pbxt/N323u1ljtNYyyaLrgw0ZLmXgepvWlBvxbJWi3sAa2VDPuNus/src_video.mp4", speed_mode: "Extra Juiced 🚀 (even more speed)", sample_shift: 16, sample_steps: 50, sample_solver: "unipc", src_ref_images: ["https://replicate.delivery/pbxt/N323t5X69JB1MPD4w4cDIxK4rm0BG0W2JOWBrDrR4O9HTcyp/src_ref_image_1.png"], sample_guide_scale: 5 } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", 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 prunaai/vace-14b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "prunaai/vace-14b:bbafc615de3e3903470a335f94294810ced166309adcba307ac8692113a7b273", input={ "seed": -1, "size": "1280*720", "prompt": "The video shows a man riding a horse on a vast grassland. He has long lavender hair and wears a traditional dress of a white top and black pants. The animation style makes him look like he is doing some kind of outdoor activity or performing. The background is a spectacular mountain range and cloud sky, giving a sense of tranquility and vastness. The entire video is shot from a fixed angle, focusing on the rider and his horse.", "src_mask": "https://replicate.delivery/pbxt/N323tegI7AuoZmg0U5CuTKa7VBFC4gymhe0kT8Jk3o2sjUUj/src_mask.mp4", "frame_num": 81, "src_video": "https://replicate.delivery/pbxt/N323u1ljtNYyyaLrgw0ZLmXgepvWlBvxbJWi3sAa2VDPuNus/src_video.mp4", "speed_mode": "Extra Juiced 🚀 (even more speed)", "sample_shift": 16, "sample_steps": 50, "sample_solver": "unipc", "src_ref_images": ["https://replicate.delivery/pbxt/N323t5X69JB1MPD4w4cDIxK4rm0BG0W2JOWBrDrR4O9HTcyp/src_ref_image_1.png"], "sample_guide_scale": 5 } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())To learn more, take a look at the guide on getting started with Python.
Run prunaai/vace-14b 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": "prunaai/vace-14b:bbafc615de3e3903470a335f94294810ced166309adcba307ac8692113a7b273", "input": { "seed": -1, "size": "1280*720", "prompt": "The video shows a man riding a horse on a vast grassland. He has long lavender hair and wears a traditional dress of a white top and black pants. The animation style makes him look like he is doing some kind of outdoor activity or performing. The background is a spectacular mountain range and cloud sky, giving a sense of tranquility and vastness. The entire video is shot from a fixed angle, focusing on the rider and his horse.", "src_mask": "https://replicate.delivery/pbxt/N323tegI7AuoZmg0U5CuTKa7VBFC4gymhe0kT8Jk3o2sjUUj/src_mask.mp4", "frame_num": 81, "src_video": "https://replicate.delivery/pbxt/N323u1ljtNYyyaLrgw0ZLmXgepvWlBvxbJWi3sAa2VDPuNus/src_video.mp4", "speed_mode": "Extra Juiced 🚀 (even more speed)", "sample_shift": 16, "sample_steps": 50, "sample_solver": "unipc", "src_ref_images": ["https://replicate.delivery/pbxt/N323t5X69JB1MPD4w4cDIxK4rm0BG0W2JOWBrDrR4O9HTcyp/src_ref_image_1.png"], "sample_guide_scale": 5 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-05-21T15:32:53.506214Z", "created_at": "2025-05-21T15:28:38.921000Z", "data_removed": false, "error": null, "id": "msg1c3g015rm80cpydv92x8jf0", "input": { "seed": -1, "size": "1280*720", "prompt": "The video shows a man riding a horse on a vast grassland. He has long lavender hair and wears a traditional dress of a white top and black pants. The animation style makes him look like he is doing some kind of outdoor activity or performing. The background is a spectacular mountain range and cloud sky, giving a sense of tranquility and vastness. The entire video is shot from a fixed angle, focusing on the rider and his horse.", "src_mask": "https://replicate.delivery/pbxt/N323tegI7AuoZmg0U5CuTKa7VBFC4gymhe0kT8Jk3o2sjUUj/src_mask.mp4", "frame_num": 81, "src_video": "https://replicate.delivery/pbxt/N323u1ljtNYyyaLrgw0ZLmXgepvWlBvxbJWi3sAa2VDPuNus/src_video.mp4", "speed_mode": "Extra Juiced 🚀 (even more speed)", "sample_shift": 16, "sample_steps": 50, "sample_solver": "unipc", "src_ref_images": [ "https://replicate.delivery/pbxt/N323t5X69JB1MPD4w4cDIxK4rm0BG0W2JOWBrDrR4O9HTcyp/src_ref_image_1.png" ], "sample_guide_scale": 5 }, "logs": "/tmp/tmphuafpq5csrc_video.mp4\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:18<14:53, 18.23s/it]\n 4%|▍ | 2/50 [00:28<10:42, 13.39s/it]\n 6%|▌ | 3/50 [00:38<09:17, 11.86s/it]\n 8%|▊ | 4/50 [00:48<08:33, 11.16s/it]\n 10%|█ | 5/50 [00:58<08:03, 10.75s/it]\n 12%|█▏ | 6/50 [01:08<07:42, 10.51s/it]\n 14%|█▍ | 7/50 [01:18<07:25, 10.35s/it]\n 18%|█▊ | 9/50 [01:28<05:18, 7.78s/it]\n 22%|██▏ | 11/50 [01:38<04:19, 6.65s/it]\n 26%|██▌ | 13/50 [01:48<03:44, 6.06s/it]\n 34%|███▍ | 17/50 [01:58<02:20, 4.25s/it]\n 42%|████▏ | 21/50 [02:08<01:41, 3.52s/it]\n 48%|████▊ | 24/50 [02:18<01:30, 3.47s/it]\n 56%|█████▌ | 28/50 [02:28<01:08, 3.11s/it]\n 68%|██████▊ | 34/50 [02:39<00:39, 2.48s/it]\n 76%|███████▌ | 38/50 [02:49<00:29, 2.49s/it]\n 84%|████████▍ | 42/50 [02:59<00:19, 2.50s/it]\n 92%|█████████▏| 46/50 [03:09<00:10, 2.51s/it]\n 96%|█████████▌| 48/50 [03:19<00:05, 2.95s/it]\n 98%|█████████▊| 49/50 [03:29<00:03, 3.75s/it]\n100%|██████████| 50/50 [03:29<00:00, 4.19s/it]", "metrics": { "predict_time": 254.572624592, "total_time": 254.585214 }, "output": "https://replicate.delivery/xezq/C3yTO4cNy45TOlUdAhJLV9oQdm7cFkVQVst0G8hVKCVJkuLF/output.mp4", "started_at": "2025-05-21T15:28:38.933590Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-hbob6mfhiqm3lte474gw7hsc4xpfdslw6vwr5st3pxsf6kmm2hja", "get": "https://api.replicate.com/v1/predictions/msg1c3g015rm80cpydv92x8jf0", "cancel": "https://api.replicate.com/v1/predictions/msg1c3g015rm80cpydv92x8jf0/cancel" }, "version": "bbafc615de3e3903470a335f94294810ced166309adcba307ac8692113a7b273" }Generated in/tmp/tmphuafpq5csrc_video.mp4 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:18<14:53, 18.23s/it] 4%|▍ | 2/50 [00:28<10:42, 13.39s/it] 6%|▌ | 3/50 [00:38<09:17, 11.86s/it] 8%|▊ | 4/50 [00:48<08:33, 11.16s/it] 10%|█ | 5/50 [00:58<08:03, 10.75s/it] 12%|█▏ | 6/50 [01:08<07:42, 10.51s/it] 14%|█▍ | 7/50 [01:18<07:25, 10.35s/it] 18%|█▊ | 9/50 [01:28<05:18, 7.78s/it] 22%|██▏ | 11/50 [01:38<04:19, 6.65s/it] 26%|██▌ | 13/50 [01:48<03:44, 6.06s/it] 34%|███▍ | 17/50 [01:58<02:20, 4.25s/it] 42%|████▏ | 21/50 [02:08<01:41, 3.52s/it] 48%|████▊ | 24/50 [02:18<01:30, 3.47s/it] 56%|█████▌ | 28/50 [02:28<01:08, 3.11s/it] 68%|██████▊ | 34/50 [02:39<00:39, 2.48s/it] 76%|███████▌ | 38/50 [02:49<00:29, 2.49s/it] 84%|████████▍ | 42/50 [02:59<00:19, 2.50s/it] 92%|█████████▏| 46/50 [03:09<00:10, 2.51s/it] 96%|█████████▌| 48/50 [03:19<00:05, 2.95s/it] 98%|█████████▊| 49/50 [03:29<00:03, 3.75s/it] 100%|██████████| 50/50 [03:29<00:00, 4.19s/it]
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