Text-to-Speech
Transformers
Safetensors
Kabyle
matoub
feature-extraction
kabyle
taqbaylit
berber
amazigh
speech-synthesis
styletts2
low-resource
custom_code
Instructions to use agbalu/Matoub-82M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use agbalu/Matoub-82M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="agbalu/Matoub-82M", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("agbalu/Matoub-82M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "added_tokens_decoder": { | |
| "0": { | |
| "content": "$", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| } | |
| }, | |
| "backend": "custom", | |
| "bos_token": "$", | |
| "eos_token": "$", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "$", | |
| "tokenizer_class": "MatoubTokenizer", | |
| "auto_map": { | |
| "AutoTokenizer": [ | |
| "tokenization_matoub.MatoubTokenizer", | |
| null | |
| ] | |
| } | |
| } | |