Feature Extraction
Diffusers
Safetensors
English
divae
terramind
remote-sensing
earth-observation
tokenizer
sentinel-1
vq
fsq
custom_code
Instructions to use BiliSakura/TerraMind-1.0-Tokenizer-S1RTC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BiliSakura/TerraMind-1.0-Tokenizer-S1RTC with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BiliSakura/TerraMind-1.0-Tokenizer-S1RTC", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0d9f8a4ce4928c066169e32f580b313a081f8870598165792e6994bad3b71dd3
- Size of remote file:
- 1.15 GB
- SHA256:
- af825f3193faccd245dd321f7d2ad512e8d54b65bc4833f214130b6a5863af19
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