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--- |
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license: apache-2.0 |
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language: |
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- en |
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library_name: transformers |
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tags: |
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- bert |
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- information retrieval |
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- learned sparse model |
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--- |
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Paper: [DeeperImpact: Optimizing Sparse Learned Index Structures](https://arxiv.org/abs/2405.17093) |
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This repository contains the DeeperImpact model trained on the MS-MARCO passage dataset expanded using a [fine-tuned Llama 2 model](https://huggingface.co/soyuj/llama2-doc2query) |
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with hard negatives, distillation, and pre-trained CoCondenser model initialization. |
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The code to train and run inferences using DeeperImpact can be found in the [DeeperImpact Repo](https://github.com/basnetsoyuj/improving-learned-index). |
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Please refer to the following notebook to understand how to use the model: [inference_deeper_impact.ipynb](https://github.com/basnetsoyuj/improving-learned-index/blob/master/inference_deeper_impact.ipynb) |
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For running inference on a larger collection of documents, use the following command: |
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```bash |
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python -m src.deep_impact.index \ |
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--collection_path <expanded_collection.tsv> \ |
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--output_file_path <path> \ |
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--model_checkpoint_path soyuj/deeper-impact \ |
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--num_processes <n> \ |
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--process_batch_size <process_batch_size> \ |
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--model_batch_size <model_batch_size> |
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``` |
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It distributes the inference across multiple GPUs in the machine. To manually set the GPUs, use `CUDA_VISIBLE_DEVICES` environment variable. |
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