Instructions to use marco83462/mi_modelo_entrenado with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use marco83462/mi_modelo_entrenado with PEFT:
Task type is invalid.
- Transformers
How to use marco83462/mi_modelo_entrenado with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="marco83462/mi_modelo_entrenado")# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("marco83462/mi_modelo_entrenado") model = AutoModelForTextToWaveform.from_pretrained("marco83462/mi_modelo_entrenado", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Configuration Parsing Warning:In adapter_config.json: "peft.task_type" must be a string
mi_modelo_entrenado
This model is a fine-tuned version of facebook/musicgen-small on the MARCO83462/DATASET_MUSICA_LORA - NA 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: 0.0002
- train_batch_size: 1
- eval_batch_size: 8
- seed: 456
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4.0
Training results
Framework versions
- PEFT 0.19.1
- Transformers 5.13.1
- Pytorch 2.13.0+cpu
- Datasets 2.21.0
- Tokenizers 0.22.2
- Downloads last month
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Model tree for marco83462/mi_modelo_entrenado
Base model
facebook/musicgen-small