Instructions to use lopho/Wan2.2-T2V-A14B-Diffusers_fp32_text_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lopho/Wan2.2-T2V-A14B-Diffusers_fp32_text_encoder with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("lopho/Wan2.2-T2V-A14B-Diffusers_fp32_text_encoder") model = AutoModel.from_pretrained("lopho/Wan2.2-T2V-A14B-Diffusers_fp32_text_encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 076cf55cb3cb2a2e1827f0160636beb41b7ddfb181cd65d8dcfff7650fc17eae
- Size of remote file:
- 22.7 GB
- SHA256:
- 01639ebebe5bd6da34562eaaca3bc364426fe07512657ce3921b4bf45ef86a95
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