
# TempoFunk Small

7.8k samples of metadata and encoded latents & prompts of random videos.

## Data format
- Video frame latents
  - Numpy arrays 
  - 120 frames, 512x512 source size
  - Encoded shape (120, 4, 64, 64)
- CLIP (openai) encoded prompts
  - Video description (as seen in metadata)
  - Encoded shape (77,768)
- Video metadata as JSON (description, tags, categories, source URL, etc.)
task_categories:text-to-video task_categories:text-to-image task_categories:video-classification task_categories:image-classification size_categories:1K<n<10K language:en license:agpl-3.0 region:us
{"language": ["en"], "license": "agpl-3.0", "size_categories": ["1K<n<10K"], "task_categories": ["text-to-video", "text-to-image", "video-classification", "image-classification"]}
TAGS
#task_categories-text-to-video #task_categories-text-to-image #task_categories-video-classification #task_categories-image-classification #size_categories-1K<n<10K #language-English #license-agpl-3.0 #region-us 


# TempoFunk Small

7.8k samples of metadata and encoded latents & prompts of random videos.

## Data format
- Video frame latents
  - Numpy arrays 
  - 120 frames, 512x512 source size
  - Encoded shape (120, 4, 64, 64)
- CLIP (openai) encoded prompts
  - Video description (as seen in metadata)
  - Encoded shape (77,768)
- Video metadata as JSON (description, tags, categories, source URL, etc.)
# TempoFunk Small

7.8k samples of metadata and encoded latents & prompts of random videos. ## Data format
- Video frame latents
  - Numpy arrays 
  - 120 frames, 512x512 source size
  - Encoded shape (120, 4, 64, 64)
- CLIP (openai) encoded prompts
  - Video description (as seen in metadata)
  - Encoded shape (77,768)
- Video metadata as JSON (description, tags, categories, source URL, etc.)
TAGS
#task_categories-text-to-video #task_categories-text-to-image #task_categories-video-classification #task_categories-image-classification #size_categories-1K<n<10K #language-English #license-agpl-3.0 #region-us 
 # TempoFunk Small

7.8k samples of metadata and encoded latents & prompts of random videos. ## Data format
- Video frame latents
  - Numpy arrays 
  - 120 frames, 512x512 source size
  - Encoded shape (120, 4, 64, 64)
- CLIP (openai) encoded prompts
  - Video description (as seen in metadata)
  - Encoded shape (77,768)
- Video metadata as JSON (description, tags, categories, source URL, etc.)