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 postnorm/checkpoint-309125/model_ema/diffusion_pytorch_model.safetensors with huggingface_hub
Browse files
postnorm/checkpoint-309125/model_ema/diffusion_pytorch_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:8ff125428151351210ae31e71f2289d815b75c4cc01cf4936d7e6c1e42b0e162
|
| 3 |
+
size 4513749856
|