Text-to-Speech
Transformers
Safetensors
Spanish
Catalan
English
qwen3
feature-extraction
text-generation-inference
Instructions to use ebellob/qwav3_4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ebellob/qwav3_4B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="ebellob/qwav3_4B")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ebellob/qwav3_4B") model = AutoModel.from_pretrained("ebellob/qwav3_4B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ebellob/qwav3_4B: direct link, hf CLI and curl.
- Browser
- Download file 12.2 MB
-
https://huggingface.co/ebellob/qwav3_4B/resolve/main/tokenizer.json
- Command line
-
hf download hf://ebellob/qwav3_4B/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ebellob/qwav3_4B/resolve/main/tokenizer.json
12.2 MB
- Xet hash:
- 9253f2132623b7d8a3840d2b3d06edc7bbef48915df1325ed99226b3160336c1
- Size of remote file:
- 12.2 MB
- SHA256:
- a335019cd4cbe0dd31da23c7df3120c08ec4b494c1d9e1b648081ff20d3948cc
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