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
File size: 482 Bytes
e044cab | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | {
"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
]
}
}
|