Instructions to use ViTeX-Bench/ViTeX-Edit-14B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ViTeX-Bench/ViTeX-Edit-14B with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ViTeX-Bench/ViTeX-Edit-14B", 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: 1,093 Bytes
bc8c4af | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | def FluxIpAdapterStateDictConverter(state_dict):
state_dict_ = {}
if "ip_adapter" in state_dict and isinstance(state_dict["ip_adapter"], dict):
for name, param in state_dict["ip_adapter"].items():
name_ = 'ipadapter_modules.' + name
state_dict_[name_] = param
if "image_proj" in state_dict:
for name, param in state_dict["image_proj"].items():
name_ = "image_proj." + name
state_dict_[name_] = param
return state_dict_
for key, value in state_dict.items():
if key.startswith("image_proj."):
state_dict_[key] = value
elif key.startswith("ip_adapter."):
new_key = key.replace("ip_adapter.", "ipadapter_modules.")
state_dict_[new_key] = value
else:
pass
return state_dict_
def SiglipStateDictConverter(state_dict):
new_state_dict = {}
for key in state_dict:
if key.startswith("vision_model."):
new_state_dict[key] = state_dict[key]
return new_state_dict |