--- license: mit language: - en metrics: - perplexity --- # CLEX: Continuous Length Extrapolation for Large Language Models This repo stores the checkpoint of CLEX-7B-16K ## Features and Highlights of CLEX ![CLEX_diagram](https://github.com/DAMO-NLP-SG/CLEX/assets/18526640/063ffe34-0116-4759-92bf-e22fc7264cdf) - **Simple and Clear**: _MINIMAL_ code and architecture changes. Only one up-and-down projection layer introduced, _NO_ recurrent memory caching or sparse attention required. - **Train Short, Test Long**: _NO_ performance drop on the sequences _4x~8x longer_ than the training ones (see [here](https://github.com/DAMO-NLP-SG/CLEX#language-modelling)). - **Continuous Length Extrapolation**: Explicitly modeling the continuous dynamics of context window size during length extrapolation. More details about long-text modeling with our CLEX can be found at the git [repo](https://github.com/DAMO-NLP-SG/CLEX). ## Model Zoo | Model Name | Model Type | Starting Point | Train Data |Train Length | MAX Test Length | |:-----|:-----|:-----------|:-----------|:-----------|:-----------| | CLEX-7B-4K | base | LLaMA-2-7B | [Redpajama-Book](https://huggingface.co/datasets/togethercomputer/RedPajama-Data-1T) | 4K | 16K | | CLEX-7B-Chat-4K | chat | CLEX-7B-4K | [UltraChat](https://github.com/thunlp/UltraChat) | 4K | 16K | | **CLEX-7B-16K** (this checkpoint) | base | LLaMA-2-7B | [Redpajama-Book](https://huggingface.co/datasets/togethercomputer/RedPajama-Data-1T) | 16K | 64K | | CLEX-7B-Chat-16K | chat | CLEX-7B-16K | [UltraChat](https://github.com/thunlp/UltraChat) | 16K | 64K | ## How to Use ```bash import torch from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("DAMO-NLP-SG/CLEX-7B-16K", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("DAMO-NLP-SG/CLEX-7B-16K", torch_dtype=torch.bfloat16, trust_remote_code=True) inputs = tokenizer("What is CLEX?", return_tensors="pt") sample = model.generate(**inputs, max_length=128) print(tokenizer.decode(sample[0])) ``` ## Citation If you find our project useful, hope you can star our repo and cite our paper as follows: ``` @article{damonlpsg2023clex, author = {Chen, Guanzheng and Li, Xin and Meng, Zaiqiao and Liang, Shangsong and Bing, Lidong}, title = {CLEX: Continuous Length Extrapolation for Large Language Models}, year = 2023, journal = {arXiv preprint arXiv:2310.16450}, url = {https://arxiv.org/abs/2310.16450} }