Text-to-Speech
Transformers
ONNX
Safetensors
multimodal
audio
video
conversational
full-duplex
function-calling
gander
Instructions to use lingyuxing/Gander with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lingyuxing/Gander with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="lingyuxing/Gander")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lingyuxing/Gander", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download thinker/NOTICE from lingyuxing/Gander: direct link, hf CLI and curl.
- Browser
- Download file 290 Bytes
-
https://huggingface.co/lingyuxing/Gander/resolve/main/thinker/NOTICE
- Command line
-
hf download hf://lingyuxing/Gander/thinker/NOTICE
-
curl -L -o NOTICE https://huggingface.co/lingyuxing/Gander/resolve/main/thinker/NOTICE
290 Bytes
| Gander v63 Unit-8 Thinker | |
| This release is derived from openbmb/MiniCPM-o-4_5, developed by OpenBMB. | |
| The upstream model and code are distributed under the Apache License 2.0. | |
| The included MiniCPM-o model code and frozen model parameters retain their | |
| upstream copyright and license notices. | |