Instructions to use chenzeyang1/T with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use chenzeyang1/T with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("chenzeyang1/T", torch_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
| import os | |
| from .clip_encoder import CLIPVisionTower, CLIPVisionTowerS2 | |
| def build_vision_tower(vision_tower_cfg, **kwargs): | |
| vision_tower = getattr(vision_tower_cfg, 'mm_vision_tower', getattr(vision_tower_cfg, 'vision_tower', None)) | |
| is_absolute_path_exists = os.path.exists(vision_tower) | |
| use_s2 = getattr(vision_tower_cfg, 's2', False) | |
| if is_absolute_path_exists or vision_tower.startswith("openai") or vision_tower.startswith("laion") or "ShareGPT4V" in vision_tower: | |
| if use_s2: | |
| return CLIPVisionTowerS2(vision_tower, args=vision_tower_cfg, **kwargs) | |
| else: | |
| return CLIPVisionTower(vision_tower, args=vision_tower_cfg, **kwargs) | |
| raise ValueError(f'Unknown vision tower: {vision_tower}') | |