Instructions to use oof-baroomf/MuseMistral-v3-35k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use oof-baroomf/MuseMistral-v3-35k with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1") model = PeftModel.from_pretrained(base_model, "oof-baroomf/MuseMistral-v3-35k") - Notebooks
- Google Colab
- Kaggle
MuseMistral-v3-35k
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1
Model description
This model generates classical music in ABC notation with only 7B parameters and internet data related to ABC notation.
Training procedure
Trained on free GPUs provided by Kaggle using Axolotl.
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 1
- eval_batch_size: 8
- seed: 3407
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- training_steps: 1000
- mixed_precision_training: Native AMP
Framework versions
- PEFT 0.7.1
- Transformers 4.36.0
- Pytorch 2.1.2
- Datasets 2.16.0
- Tokenizers 0.15.0
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Model tree for oof-baroomf/MuseMistral-v3-35k
Base model
mistralai/Mistral-7B-v0.1