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chtmp223/ProLong-512k-8B-WritingPrompts
ProLong-512k-8B-WritingPrompts is a machine learning model from chtmp223. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
ProLong-512k-8B-CLIPPER is a fine-tuned version of princeton-nlp/Llama-3-8B-ProLong-512k-Instruct using supervised finetuning over chtmp223/CLIPPER dataset. Please check our paper for more details on the method.
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From the Hugging Face model README
ProLong-512k-8B-CLIPPER is a fine-tuned version of princeton-nlp/Llama-3-8B-ProLong-512k-Instruct using supervised finetuning over chtmp223/CLIPPER dataset. Please check our paper for more details on the method.
chtmp223/CLIPPER-WritingPrompts
| Configurations | Values |
|---|---|
| Hardware (Training and Inference) | 8xA100s |
| Tracking | wandb |
| batch size | 16 |
| gradient_checkpointing | True |
| learning_rate | 1.0e-5 |
| lr_scheduler_type | cosine |
| max_length | 131072 |
| num_train_epochs | 1 |
| optim | adamw_torch |
Training code is adapted from https://github.com/princeton-nlp/ProLong.
Inference is done with vLLM on 1 A100-80GB.
@misc{pham2025clippercompressionenableslongcontext,
title={CLIPPER: Compression enables long-context synthetic data generation},
author={Chau Minh Pham and Yapei Chang and Mohit Iyyer},
year={2025},
eprint={2502.14854},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2502.14854},
}