Instructions to use williamplacroix/text-simplification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use williamplacroix/text-simplification with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "williamplacroix/text-simplification") - Notebooks
- Google Colab
- Kaggle
| library_name: peft | |
| license: mit | |
| base_model: openai-community/gpt2 | |
| tags: | |
| - generated_from_trainer | |
| model-index: | |
| - name: text-simplification | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/uds/Graded%20text%20simplification%20training/runs/0wk7divh) | |
| # text-simplification | |
| This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co/openai-community/gpt2) on the None dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.5713 | |
| ## 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: 16 | |
| - seed: 42 | |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments | |
| - lr_scheduler_type: linear | |
| - num_epochs: 5 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | | |
| |:-------------:|:-----:|:-----:|:---------------:| | |
| | 0.884 | 1.0 | 6044 | 0.6113 | | |
| | 0.6392 | 2.0 | 12088 | 0.5825 | | |
| | 0.6168 | 3.0 | 18132 | 0.5764 | | |
| | 0.6077 | 4.0 | 24176 | 0.5732 | | |
| | 0.6038 | 5.0 | 30220 | 0.5713 | | |
| ### Framework versions | |
| - PEFT 0.14.0 | |
| - Transformers 4.48.3 | |
| - Pytorch 2.6.0+cu124 | |
| - Datasets 3.2.0 | |
| - Tokenizers 0.21.0 |