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camenduru /streaming-t2v:1fe245aa
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=camenduru/streaming-t2v
or set up a project from scratch
npm install replicateSet the
REPLICATE_API_TOKEN environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client
import Replicate from "replicate";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});Run camenduru/streaming-t2v using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"camenduru/streaming-t2v:1fe245aad4bb7f209074a231142ac3eceb3b1f2adc9cf77b46e8ffa2662323cf",
{
input: {
seed: 33,
chunk: 24,
prompt: "Experience the dance of jellyfish: float through mesmerizing swarms of jellyfish, pulsating with otherworldly grace and beauty.",
enhance: true,
overlap: 8,
num_steps: 50,
num_frames: 120,
image_guidance: 9,
negative_prompt: ""
}
}
);
console.log(output);To learn more, take a look at the guide on getting started with Node.js.
pip install replicateSet the
REPLICATE_API_TOKEN environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client
import replicateRun camenduru/streaming-t2v using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"camenduru/streaming-t2v:1fe245aad4bb7f209074a231142ac3eceb3b1f2adc9cf77b46e8ffa2662323cf",
input={
"seed": 33,
"chunk": 24,
"prompt": "Experience the dance of jellyfish: float through mesmerizing swarms of jellyfish, pulsating with otherworldly grace and beauty.",
"enhance": True,
"overlap": 8,
"num_steps": 50,
"num_frames": 120,
"image_guidance": 9,
"negative_prompt": ""
}
)
print(output)To learn more, take a look at the guide on getting started with Python.
Set the
REPLICATE_API_TOKEN environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run camenduru/streaming-t2v 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": "1fe245aad4bb7f209074a231142ac3eceb3b1f2adc9cf77b46e8ffa2662323cf",
"input": {
"seed": 33,
"chunk": 24,
"prompt": "Experience the dance of jellyfish: float through mesmerizing swarms of jellyfish, pulsating with otherworldly grace and beauty.",
"enhance": true,
"overlap": 8,
"num_steps": 50,
"num_frames": 120,
"image_guidance": 9,
"negative_prompt": ""
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Install Cog
brew install cogIf you don’t have Homebrew, there are other installation options available.
Pull and run camenduru/streaming-t2v using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/camenduru/streaming-t2v@sha256:1fe245aad4bb7f209074a231142ac3eceb3b1f2adc9cf77b46e8ffa2662323cf \
-i 'seed=33' \
-i 'chunk=24' \
-i 'prompt="Experience the dance of jellyfish: float through mesmerizing swarms of jellyfish, pulsating with otherworldly grace and beauty."' \
-i 'enhance=true' \
-i 'overlap=8' \
-i 'num_steps=50' \
-i 'num_frames=120' \
-i 'image_guidance=9' \
-i 'negative_prompt=""'To learn more, take a look at the Cog documentation.
Pull and run camenduru/streaming-t2v using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 r8.im/camenduru/streaming-t2v@sha256:1fe245aad4bb7f209074a231142ac3eceb3b1f2adc9cf77b46e8ffa2662323cfcurl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "seed": 33, "chunk": 24, "prompt": "Experience the dance of jellyfish: float through mesmerizing swarms of jellyfish, pulsating with otherworldly grace and beauty.", "enhance": true, "overlap": 8, "num_steps": 50, "num_frames": 120, "image_guidance": 9, "negative_prompt": "" } }' \ http://localhost:5000/predictions
Add a payment method to run this model.
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Output
{
"completed_at": "2024-04-10T05:21:57.916845Z",
"created_at": "2024-04-10T05:12:36.264000Z",
"data_removed": false,
"error": null,
"id": "j81wsngpn1rgc0cerspazkgs6m",
"input": {
"seed": 33,
"chunk": 24,
"prompt": "Experience the dance of jellyfish: float through mesmerizing swarms of jellyfish, pulsating with otherworldly grace and beauty.",
"enhance": true,
"overlap": 8,
"num_steps": 50,
"num_frames": 120,
"image_guidance": 9,
"negative_prompt": ""
},
"logs": "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n/usr/local/lib/python3.10/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:442: PossibleUserWarning: The dataloader, predict_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 48 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.\nrank_zero_warn(\nINFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}\nINFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}\nINFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}\nINFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}\nINFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}\nINFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}\nINFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}\nINFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}\nINFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}\nINFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}\nINFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}\nINFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}\nINFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}\nPredicting ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1/1 0:06:16 • 0:00:00 0.00it/s\n/usr/local/lib/python3.10/site-packages/torchsde/_brownian/brownian_interval.py:608: UserWarning: Should have tb<=t1 but got tb=4.164773464202881 and t1=4.164773.\nwarnings.warn(f\"Should have {tb_name}<=t1 but got {tb_name}={tb} and t1={self._end}.\")",
"metrics": {
"predict_time": 561.635751,
"total_time": 561.652845
},
"output": [
"https://replicate.delivery/pbxt/DmwNVZX9sd41EZZpO5cf8GgS4wtVs9WM0DEncQdvsSe1P9oSA/output.mp4",
"https://replicate.delivery/pbxt/TGxCwYt5I16LLhxOpUUEpDio8RfOofpKwV281XDz9921P9oSA/output_enhanced.mp4"
],
"started_at": "2024-04-10T05:12:36.281094Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/j81wsngpn1rgc0cerspazkgs6m",
"cancel": "https://api.replicate.com/v1/predictions/j81wsngpn1rgc0cerspazkgs6m/cancel"
},
"version": "1fe245aad4bb7f209074a231142ac3eceb3b1f2adc9cf77b46e8ffa2662323cf"
}Generated in
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
/usr/local/lib/python3.10/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:442: PossibleUserWarning: The dataloader, predict_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 48 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.
rank_zero_warn(
INFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}
INFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}
INFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}
INFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}
INFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}
INFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}
INFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}
INFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}
INFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}
INFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}
INFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}
INFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}
INFERENCE PARAMS = {'concat_video': True, 'conditioning_from_all_past': False, 'conditioning_type': 'fixed', 'eta': 1.0, 'eval_loss_metrics': False, 'frame_rate': 8, 'guidance_scale': 7.5, 'height': 256, 'mode': 'long_video', 'n_autoregressive_generations': 4, 'negative_prompt': '', 'num_inference_steps': 50, 'result_formats': ['eval_mp4'], 'scheduler_cls': '', 'seed': 33, 'start_from_real_input': False, 'use_dec_scaling': True, 'validation_samples': 80, 'video_length': 16, 'width': 256}
Predicting ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1/1 0:06:16 • 0:00:00 0.00it/s
/usr/local/lib/python3.10/site-packages/torchsde/_brownian/brownian_interval.py:608: UserWarning: Should have tb<=t1 but got tb=4.164773464202881 and t1=4.164773.
warnings.warn(f"Should have {tb_name}<=t1 but got {tb_name}={tb} and t1={self._end}.")