Image-to-Image
Transformers
Safetensors
in-image-machine-translation
image-translation
image-editing
multimodal
qwen2.5-vl
flux
Instructions to use SeerRay-Lab/Unitranslator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SeerRay-Lab/Unitranslator with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-image" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("image-to-image", model="SeerRay-Lab/Unitranslator")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SeerRay-Lab/Unitranslator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download random_states_2.pkl from SeerRay-Lab/Unitranslator: direct link, hf CLI and curl.
- Browser
- Download file 16.5 kB
-
https://huggingface.co/SeerRay-Lab/Unitranslator/resolve/main/random_states_2.pkl
- Command line
-
hf download hf://SeerRay-Lab/Unitranslator/random_states_2.pkl
-
curl -L -o random_states_2.pkl https://huggingface.co/SeerRay-Lab/Unitranslator/resolve/main/random_states_2.pkl
16.5 kB
- Xet hash:
- a591b8064355ca1e8332a4ffc2b45e35b562311f20cb1a3ce038e62b4ee0269d
- Size of remote file:
- 16.5 kB
- SHA256:
- ec6b63ec734ecee648798e82822924891f8d8249d341b06d12f9be3252348245
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