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‎CONTRIBUTING.md

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<!--- Licensed to the Apache Software Foundation (ASF) under one -->
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<!--- or more contributor license agreements. See the NOTICE file -->
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<!--- distributed with this work for additional information -->
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<!--- regarding copyright ownership. The ASF licenses this file -->
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<!--- to you under the Apache License, Version 2.0 (the -->
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<!--- "License"); you may not use this file except in compliance -->
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<!--- with the License. You may obtain a copy of the License at -->
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<!--- http://www.apache.org/licenses/LICENSE-2.0 -->
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<!--- Unless required by applicable law or agreed to in writing, -->
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<!--- software distributed under the License is distributed on an -->
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<!--- "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY -->
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<!--- KIND, either express or implied. See the License for the -->
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<!--- specific language governing permissions and limitations -->
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<!--- under the License. -->
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# How to Contribute
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We'd love to accept your patches and contributions to this project. There are
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just a few small guidelines you need to follow.
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## Contributor License Agreement
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Contributions to this project must be accompanied by a Contributor License
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## Changes Accepted
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## Issues
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‎LICENSE

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‎README.md

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<div align="center">
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<h1><img src="static/images/ShadowKV.png" height="40px"> ShadowKV</h1>
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</div>
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<div align="center">
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<b><a href="https://github.com/preminstrel">Hanshi Sun</a></b><sup>1,2</sup>,
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<b><a href="https://lchang20.github.io/">Li-Wen Chang</a></b><sup>2</sup>,
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<b><a href="https://sites.google.com/view/wenleibao/">Wenlei Bao</a></b><sup>2</sup>,
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<b><a href="https://sizezheng.github.io/">Size Zheng</a></b><sup>2</sup>,
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<b><a href="https://zheng-ningxin.github.io/">Ningxin Zheng</a></b><sup>2</sup>,
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<br>
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<b><a href="https://github.com/preminstrel">Harry Dong</a></b><sup>1</sup>,
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<b><a href="https://github.com/preminstrel">Yuejie Chi</a></b><sup>1</sup>,
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<b><a href="https://github.com/preminstrel">Beidi Chen</a></b><sup>1</sup>
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</div>
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<div align="center">
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<sup>1</sup>Carnegie Mellon University
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<sup>2</sup>ByteDance
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</div>
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<div align="center">
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[<a href="XXXX">Paper</a>] | [<a href="XXXX">Blog</a>]
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</div>
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<br>
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<div align="center">
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<img src="static/images/framework.png" align="top"/>
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<figcaption>ShadowKV Framework</figcaption>
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</div>
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## Environment Set Up
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```bash
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# create env
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conda create -n ShadowKV python=3.10 -y
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conda activate ShadowKV
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# install packages
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pip install -r requirements.txt
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pip install flash-attn --no-build-isolation
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# nemo dependencies (for dataset building)
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pip install wheel
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pip install Cython
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pip install youtokentome
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pip install nemo_toolkit[all]==1.23
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# flashinfer
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pip install flashinfer -i https://flashinfer.ai/whl/cu121/torch2.3/
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pip install huggingface_hub==0.22.0
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# build kernels
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python setup.py build_ext --inplace
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```
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## Supported Models
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Currently, we support the following LLMs:
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- Llama-3-8B-1M: [gradientai/Llama-3-70B-Instruct-Gradient-1048k](https://huggingface.co/gradientai/Llama-3-70B-Instruct-Gradient-1048k)
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- GLM-4-9B-1M: [THUDM/glm-4-9b-chat-1m](https://huggingface.co/THUDM/glm-4-9b-chat-1m)
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- Llama-3.1-8B: [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct)
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- Yi-9B-200K: [01-ai/Yi-9B-200K](https://huggingface.co/01-ai/Yi-9B-200K)
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- Phi-3-Mini-128K: [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct)
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- Qwen2-7B-128K: [Qwen/Qwen2-7B-Instruct](https://huggingface.co/Qwen/Qwen2-7B-Instruct)
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## Accuracy Evaluations
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Here we provide an example to build the dataset and run evaluation for the [RULER](https://github.com/hsiehjackson/RULER) benchmark with Llama-3-8B-1M.
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### Build Dataset
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```bash
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# build RULER
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python -c "import nltk; nltk.download('punkt')"
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cd data/ruler
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bash create_dataset.sh "gradientai/Llama-3-8B-Instruct-Gradient-1048k" "llama-3"
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```
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### Run Evaluation
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```bash
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# Full attention
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OMP_NUM_THREADS=48 torchrun --standalone --nnodes=1 --nproc_per_node 8 test/eval_acc.py --datalen 131072 --method full --dataset_name "ruler/niah_single_1,ruler/niah_single_2,ruler/niah_single_3,ruler/niah_multikey_1,ruler/niah_multikey_2,ruler/niah_multikey_3,ruler/niah_multiquery,ruler/niah_multivalue,ruler/vt,ruler/cwe,ruler/fwe,ruler/qa_1,ruler/qa_2" --model_name "gradientai/Llama-3-8B-Instruct-Gradient-1048k"
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# ShadowKV
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OMP_NUM_THREADS=48 torchrun --standalone --nnodes=1 --nproc_per_node 8 test/eval_acc.py --datalen 131072 --method shadowkv --dataset_name "ruler/niah_single_1,ruler/niah_single_2,ruler/niah_single_3,ruler/niah_multikey_1,ruler/niah_multikey_2,ruler/niah_multikey_3,ruler/niah_multiquery,ruler/niah_multivalue,ruler/vt,ruler/cwe,ruler/fwe,ruler/qa_1,ruler/qa_2" --sparse_budget 2048 --rank 160 --chunk_size 8
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```

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