Text-to-Speech
Transformers
PyTorch
TensorBoard
Safetensors
Spanish
speecht5
text-to-audio
mabama-tts-es
Generated from Trainer
Instructions to use ovieyra21/mabama-tts-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ovieyra21/mabama-tts-es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="ovieyra21/mabama-tts-es")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("ovieyra21/mabama-tts-es") model = AutoModelForTextToSpectrogram.from_pretrained("ovieyra21/mabama-tts-es") - Notebooks
- Google Colab
- Kaggle
mabama-tts-v1
This model is a fine-tuned version of microsoft/speecht5_tts on the mabama-v4 dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.28.0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.13.3 Download them in the Files & versions tab.
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