Text-to-Speech
Transformers
Safetensors
Kabyle
agbalu_speech
feature-extraction
kabyle
taqbaylit
berber
amazigh
speech-synthesis
voice-cloning
cross-lingual-voice-cloning
expressive-speech
low-resource
custom_code
Instructions to use agbalu/Matoub-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use agbalu/Matoub-4B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="agbalu/Matoub-4B", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("agbalu/Matoub-4B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download STAMP.json from agbalu/Matoub-4B: direct link, hf CLI and curl.
- Browser
- Download file 189 Bytes
-
https://huggingface.co/agbalu/Matoub-4B/resolve/main/STAMP.json
- Command line
-
hf download hf://agbalu/Matoub-4B/STAMP.json
-
curl -L -o STAMP.json https://huggingface.co/agbalu/Matoub-4B/resolve/main/STAMP.json
189 Bytes
| {"config_hash": "11c975e42f84cde0d25d1bb162ae5934f3e49a755fb0da95e93e60eb7f5660cd", "dirty": true, "git_sha": "4c0e119b42518dafee8be80d10d8dfdb13090295", "version": 1, "version_tag": null} | |