Instructions to use tk93/V-Express with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tk93/V-Express with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("tk93/V-Express", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Download model_ckpts/wav2vec2-base-960h/preprocessor_config.json from tk93/V-Express: direct link, hf CLI and curl.
- Browser
- Download file 159 Bytes
-
https://huggingface.co/tk93/V-Express/resolve/main/model_ckpts/wav2vec2-base-960h/preprocessor_config.json
- Command line
-
hf download hf://tk93/V-Express/model_ckpts/wav2vec2-base-960h/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/tk93/V-Express/resolve/main/model_ckpts/wav2vec2-base-960h/preprocessor_config.json
159 Bytes
| { | |
| "do_normalize": true, | |
| "feature_size": 1, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "return_attention_mask": false, | |
| "sampling_rate": 16000 | |
| } | |