---
license: apache-2.0
language:
- en
library_name: transformers
tags:
- bert
- information retrieval
- learned sparse model
---

Paper: [DeeperImpact: Optimizing Sparse Learned Index Structures](https://arxiv.org/abs/2405.17093)

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)
with hard negatives, distillation, and pre-trained CoCondenser model initialization.

The code to train and run inferences using DeeperImpact can be found in the [DeeperImpact Repo](https://github.com/basnetsoyuj/improving-learned-index).

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)

For running inference on a larger collection of documents, use the following command:

```bash
python -m src.deep_impact.index \
  --collection_path <expanded_collection.tsv> \
  --output_file_path <path> \
  --model_checkpoint_path soyuj/deeper-impact \
  --num_processes <n> \
  --process_batch_size <process_batch_size> \
  --model_batch_size <model_batch_size>
```

It distributes the inference across multiple GPUs in the machine. To manually set the GPUs, use `CUDA_VISIBLE_DEVICES` environment variable.