Instructions to use ileniaerrico/aiFT-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ileniaerrico/aiFT-model with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-base") model = PeftModel.from_pretrained(base_model, "ileniaerrico/aiFT-model") - Transformers
How to use ileniaerrico/aiFT-model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ileniaerrico/aiFT-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
aiFT-model
This model is a fine-tuned version of google/flan-t5-base on an unknown 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: 0.0005
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- 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: 1
Training results
Framework versions
- PEFT 0.19.1
- Transformers 5.8.1
- Pytorch 2.12.0+cu130
- Datasets 4.8.5
- Tokenizers 0.22.2
- Downloads last month
- 4
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Model tree for ileniaerrico/aiFT-model
Base model
google/flan-t5-base