Instructions to use vidfom/Wav2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vidfom/Wav2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("vidfom/Wav2", 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
| { | |
| "name_or_path": "THUDM/chatglm3-6b-base", | |
| "remove_space": false, | |
| "do_lower_case": false, | |
| "tokenizer_class": "ChatGLMTokenizer", | |
| "auto_map": { | |
| "AutoTokenizer": [ | |
| "tokenization_chatglm.ChatGLMTokenizer", | |
| null | |
| ] | |
| } | |
| } | |