Initial Commit
Browse files- README.md +45 -0
- config.json +39 -0
- generation_config.json +6 -0
- gitattributes +35 -0
- pytorch_model.bin +3 -0
README.md
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---
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license: cc-by-nc-nd-4.0
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---
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# Introduction
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TQCompressedGPT-2 is an advanced neural network model, offering a novel method for model compression through improved tensor decompositions. It addresses the challenges of computational and storage demands in NLP tasks, introducing a permutation-based enhancement to Kronecker decomposition, significantly reducing model size while maintaining performance.\
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TQCompressedGPT2 © 2024 by Terra Quantum AG is licensed under CC BY-NC-ND 4.0. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ \
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Any entity who wishes to use this library for commercial purposes should contact [email protected] for more information.\
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[![License: CC BY-NC-ND 4.0](https://img.shields.io/badge/License-CC%20BY--NC--ND%204.0-lightgrey.svg)](https://creativecommons.org/licenses/by-nc-nd/4.0/)\
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<img src="https://cdn-uploads.huggingface.co/production/uploads/6476003bbed7adbb05f8441f/jEKdKKFoEzlAbbI4NnokH.png" width="500">
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# Features
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**Model Size Reduction:** Compresses the GPT-2small model from 124 million to 81 million parameters.\
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**Permutation-Based Enhancement:** Introduces a new permutation algorithm for matrix factorization, minimizing performance degradation.\
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**Efficient Training Strategy:** Employs multi-step knowledge distillation with a fraction (3.1%) of the OpenWebText dataset.\
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**Performance:** Outperforms DistilGPT-2 in comparative evaluations.\
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<img src="https://cdn-uploads.huggingface.co/production/uploads/6476003bbed7adbb05f8441f/x1krVBC2RTZNDR0dynbRp.png" width="500">
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## Permutation-Based Enhancement
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In our work we employ permutation-based algorithm, which allows to achieve better decomposition approximation for weight matrices:\
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<img src="https://cdn-uploads.huggingface.co/production/uploads/6476003bbed7adbb05f8441f/bM6KwfKWYBJjeX_xGw83C.png" width="500">
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# Methodology
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For more details about the techniques of TQCompressedGPT-2, refer to our paper: **(ADD LINK)TQCompressor: Improving Tensor Decomposition in Neural Networks via Permutations**\
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**TQCompressed Decomposition:** Focuses on optimal permutation of weight matrices followed by Kronecker decomposition.\
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**Knowledge Distillation:** Uses an iterative compression method coupled with knowledge distillation, enhancing performance.\
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**Application:** Demonstrated on the GPT-2 model, showing its versatility and applicability to various neural network architectures.
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# Usage
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The model and code are publicly available at:
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- [GitHub Repository](https://github.com/terra-quantum-io/TQCompressedGPT2)
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- [HuggingFace Repository](https://huggingface.co/tq-ai-research/TQCompressedGPT2)
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# Citation
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If you find TQCompressedGPT-2 useful in your research, please cite the following paper:
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```
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@article{tqcompressedgpt2,
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title={TQCompressor: Improving Tensor Decomposition in Neural Networks via Permutations},
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author={Abronin, V., Naumov, A., Mazur, D., Bystrov, D., Tsarova, K., Melnikov, Ar., Oseledets, I., Dolgov, S., Brasher, R., Perelshtein, M.},
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journal={arXiv preprint arXiv:[insert_arxiv_id]},
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year={2023}
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}
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```
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# Acknowledgments
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- [Terra Quantum AG](https://terraquantum.swiss/), Kornhausstrasse 25, 9000 St. Gallen, Switzerland
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- Project contributors and researchers.
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config.json
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{
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"_name_or_path": "gpt2",
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"activation_function": "gelu_new",
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"architectures": [
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"GPT2LMHeadModel"
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],
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"attn_pdrop": 0.1,
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"bos_token_id": 50256,
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"embd_pdrop": 0.1,
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"eos_token_id": 50256,
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"initializer_range": 0.02,
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"layer_norm_epsilon": 1e-05,
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"model_type": "gpt2",
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"n_ctx": 1024,
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"n_embd": 768,
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"n_head": 12,
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"n_inner": null,
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"n_layer": 12,
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"n_positions": 1024,
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"reorder_and_upcast_attn": false,
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"resid_pdrop": 0.1,
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"scale_attn_by_inverse_layer_idx": false,
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"scale_attn_weights": true,
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"summary_activation": null,
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"summary_first_dropout": 0.1,
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"summary_proj_to_labels": true,
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"summary_type": "cls_index",
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"summary_use_proj": true,
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"task_specific_params": {
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"text-generation": {
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"do_sample": true,
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"max_length": 50
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}
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},
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"torch_dtype": "float32",
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"transformers_version": "4.31.0",
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"use_cache": true,
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"vocab_size": 50257
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 50256,
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"eos_token_id": 50256,
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"transformers_version": "4.31.0"
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}
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gitattributes
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:c65274bbf42607d7451261fc0a5a671bc28dc5f7ac86b77adf0e5e684ea4c75c
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size 480171457
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