Instructions to use LanguageBind/t2i_ablation_arch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use LanguageBind/t2i_ablation_arch with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("LanguageBind/t2i_ablation_arch", 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
Upload vae/prenorm_1616/checkpoint-304000/model_ema/diffusion_pytorch_model.safetensors with huggingface_hub
Browse files
vae/prenorm_1616/checkpoint-304000/model_ema/diffusion_pytorch_model.safetensors
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