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") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lingyuxing/Gander", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download thinker/tokenizer.json from lingyuxing/Gander: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/lingyuxing/Gander/resolve/main/thinker/tokenizer.json
- Command line
-
hf download hf://lingyuxing/Gander/thinker/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/lingyuxing/Gander/resolve/main/thinker/tokenizer.json
11.4 MB
- Xet hash:
- fcd57a50cc93c1b52c6c72dda0b45ef660d9f26f58f6475f93478da2df775053
- Size of remote file:
- 11.4 MB
- SHA256:
- f3402ed212a4ccc87fa8f20c80fb4d7e38b63291e465d12b4948779af53a3c3b
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