Instructions to use easylearning/FutureWorlds with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use easylearning/FutureWorlds with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("easylearning/FutureWorlds", 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
File size: 476 Bytes
64b9802 | 1 2 3 4 5 6 7 8 9 10 | """Small tensor container for the upstream video reward's batch-only API."""
class TensorBatch:
def __init__(self,batch,meta_info=None):
self.batch=batch
self.meta_info=meta_info or {}
@classmethod
def from_single_dict(cls,batch,meta_info=None):return cls(batch,meta_info)
def __len__(self):return len(next(iter(self.batch.values())))
def __getitem__(self,index):return type(self)({k:v[index] for k,v in self.batch.items()},self.meta_info)
|