Instructions to use maya-research/maya1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maya-research/maya1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="maya-research/maya1")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("maya-research/maya1") model = AutoModelForCausalLM.from_pretrained("maya-research/maya1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3273ed58228a90a2915161deef43ad19090956e8c44c2d2ee359a78eb4807056
- Size of remote file:
- 22.9 MB
- SHA256:
- 6c5e5b1d89b7e3738e5a5a4f93c326d8f3292ea83f9c560b8dbb6d66fb851973
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.