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AIR-Bench
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Running on CPU Upgrade

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2 Parent(s): 6925231 2dca7ce

Merge branch 'main' of https://huggingface.co/spaces/AIR-Bench/leaderboard

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  1. src/about.py +93 -85
src/about.py CHANGED
@@ -30,109 +30,117 @@ pip install .
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  ```bash
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  cd AIR-Bench/scripts
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  # Run all tasks
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- python run_AIR-Bench.py \
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- --output_dir ./search_results \
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  --encoder BAAI/bge-m3 \
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- --encoder_link https://huggingface.co/BAAI/bge-m3 \
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- --reranker BAAI/bge-reranker-v2-m3 \
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- --reranker_link https://huggingface.co/BAAI/bge-reranker-v2-m3 \
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- --search_top_k 1000 \
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- --rerank_top_k 100 \
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- --max_query_length 512 \
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- --max_passage_length 512 \
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- --batch_size 512 \
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- --pooling_method cls \
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- --normalize_embeddings True \
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- --use_fp16 True \
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- --add_instruction False \
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  --overwrite False
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  # Run the tasks in the specified task type
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- python run_AIR-Bench.py \
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- --task_types long-doc \
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- --output_dir ./search_results \
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- --encoder BAAI/bge-m3 \
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- --encoder_link https://huggingface.co/BAAI/bge-m3 \
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- --reranker BAAI/bge-reranker-v2-m3 \
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- --reranker_link https://huggingface.co/BAAI/bge-reranker-v2-m3 \
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- --search_top_k 1000 \
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- --rerank_top_k 100 \
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- --max_query_length 512 \
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- --max_passage_length 512 \
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- --batch_size 512 \
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- --pooling_method cls \
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- --normalize_embeddings True \
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- --use_fp16 True \
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- --add_instruction False \
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  --overwrite False
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  # Run the tasks in the specified task type and domains
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- python run_AIR-Bench.py \
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- --task_types long-doc \
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- --domains arxiv book \
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- --output_dir ./search_results \
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- --encoder BAAI/bge-m3 \
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- --encoder_link https://huggingface.co/BAAI/bge-m3 \
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- --reranker BAAI/bge-reranker-v2-m3 \
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- --reranker_link https://huggingface.co/BAAI/bge-reranker-v2-m3 \
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- --search_top_k 1000 \
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- --rerank_top_k 100 \
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- --max_query_length 512 \
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- --max_passage_length 512 \
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- --batch_size 512 \
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- --pooling_method cls \
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- --normalize_embeddings True \
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- --use_fp16 True \
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- --add_instruction False \
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  --overwrite False
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  # Run the tasks in the specified languages
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- python run_AIR-Bench.py \
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- --languages en \
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- --output_dir ./search_results \
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- --encoder BAAI/bge-m3 \
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- --encoder_link https://huggingface.co/BAAI/bge-m3 \
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- --reranker BAAI/bge-reranker-v2-m3 \
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- --reranker_link https://huggingface.co/BAAI/bge-reranker-v2-m3 \
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- --search_top_k 1000 \
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- --rerank_top_k 100 \
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- --max_query_length 512 \
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- --max_passage_length 512 \
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- --batch_size 512 \
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- --pooling_method cls \
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- --normalize_embeddings True \
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- --use_fp16 True \
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- --add_instruction False \
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  --overwrite False
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  # Run the tasks in the specified task type, domains, and languages
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- python run_AIR-Bench.py \
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- --task_types qa \
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- --domains wiki web \
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- --languages en \
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- --output_dir ./search_results \
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- --encoder BAAI/bge-m3 \
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- --encoder_link https://huggingface.co/BAAI/bge-m3 \
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- --reranker BAAI/bge-reranker-v2-m3 \
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- --reranker_link https://huggingface.co/BAAI/bge-reranker-v2-m3 \
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- --search_top_k 1000 \
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- --rerank_top_k 100 \
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- --max_query_length 512 \
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- --max_passage_length 512 \
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- --batch_size 512 \
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- --pooling_method cls \
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- --normalize_embeddings True \
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- --use_fp16 True \
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- --add_instruction False \
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  --overwrite False
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  ```
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  3. Package the search results.
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  ```bash
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- python zip_results.py \
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- --results_path search_results/bge-m3 \
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- --save_path search_results/zipped_results
 
 
 
 
 
 
 
 
 
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  ```
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- 4. Upload the `.zip` file on this page and fill in the model information.
 
 
 
 
 
 
 
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  5. Congratulation! Your results will be shown on the leaderboard in up to one hour.
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  """
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  ```bash
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  cd AIR-Bench/scripts
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  # Run all tasks
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+ python run_AIR-Bench.py \\
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+ --output_dir ./search_results \\
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  --encoder BAAI/bge-m3 \
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+ --reranker BAAI/bge-reranker-v2-m3 \\
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+ --search_top_k 1000 \\
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+ --rerank_top_k 100 \\
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+ --max_query_length 512 \\
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+ --max_passage_length 512 \\
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+ --batch_size 512 \\
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+ --pooling_method cls \\
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+ --normalize_embeddings True \\
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+ --use_fp16 True \\
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+ --add_instruction False \\
 
 
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  --overwrite False
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  # Run the tasks in the specified task type
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+ python run_AIR-Bench.py \\
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+ --task_types long-doc \\
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+ --output_dir ./search_results \\
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+ --encoder BAAI/bge-m3 \\
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+ --reranker BAAI/bge-reranker-v2-m3 \\
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+ --search_top_k 1000 \\
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+ --rerank_top_k 100 \\
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+ --max_query_length 512 \\
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+ --max_passage_length 512 \\
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+ --batch_size 512 \\
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+ --pooling_method cls \\
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+ --normalize_embeddings True \\
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+ --use_fp16 True \\
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+ --add_instruction False \\
 
 
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  --overwrite False
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  # Run the tasks in the specified task type and domains
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+ python run_AIR-Bench.py \\
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+ --task_types long-doc \\
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+ --domains arxiv book \\
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+ --output_dir ./search_results \\
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+ --encoder BAAI/bge-m3 \\
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+ --reranker BAAI/bge-reranker-v2-m3 \\
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+ --search_top_k 1000 \\
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+ --rerank_top_k 100 \\
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+ --max_query_length 512 \\
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+ --max_passage_length 512 \\
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+ --batch_size 512 \\
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+ --pooling_method cls \\
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+ --normalize_embeddings True \\
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+ --use_fp16 True \\
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+ --add_instruction False \\
 
 
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  --overwrite False
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  # Run the tasks in the specified languages
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+ python run_AIR-Bench.py \\
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+ --languages en \\
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+ --output_dir ./search_results \\
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+ --encoder BAAI/bge-m3 \\
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+ --reranker BAAI/bge-reranker-v2-m3 \\
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+ --search_top_k 1000 \\
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+ --rerank_top_k 100 \\
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+ --max_query_length 512 \\
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+ --max_passage_length 512 \\
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+ --batch_size 512 \\
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+ --pooling_method cls \\
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+ --normalize_embeddings True \\
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+ --use_fp16 True \\
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+ --add_instruction False \\
 
 
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  --overwrite False
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  # Run the tasks in the specified task type, domains, and languages
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+ python run_AIR-Bench.py \\
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+ --task_types qa \\
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+ --domains wiki web \\
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+ --languages en \\
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+ --output_dir ./search_results \\
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+ --encoder BAAI/bge-m3 \\
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+ --encoder_link https://huggingface.co/BAAI/bge-m3 \\
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+ --reranker BAAI/bge-reranker-v2-m3 \\
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+ --reranker_link https://huggingface.co/BAAI/bge-reranker-v2-m3 \\
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+ --search_top_k 1000 \\
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+ --rerank_top_k 100 \\
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+ --max_query_length 512 \\
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+ --max_passage_length 512 \\
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+ --batch_size 512 \\
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+ --pooling_method cls \\
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+ --normalize_embeddings True \\
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+ --use_fp16 True \\
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+ --add_instruction False \\
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  --overwrite False
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  ```
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  3. Package the search results.
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  ```bash
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+ # Zip "Embedding Model + NoReranker" search results in "<search_results>/<model_name>/NoReranker" to "<save_dir>/<model_name>_NoReranker.zip".
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+ python zip_results.py \\
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+ --results_dir search_results \\
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+ --model_name bge-m3 \\
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+ --save_dir search_results/zipped_results
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+
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+ # Zip "Embedding Model + Reranker" search results in "<search_results>/<model_name>/<reranker_name>" to "<save_dir>/<model_name>_<reranker_name>.zip".
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+ python zip_results.py \\
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+ --results_dir search_results \\
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+ --model_name bge-m3 \\
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+ --reranker_name bge-reranker-v2-m3 \\
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+ --save_dir search_results/zipped_results
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  ```
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+ 4. Upload the `.zip` file on this page and fill in the model information:
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+ - Model Name: such as `bge-m3`.
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+ - Model URL: such as `https://huggingface.co/BAAI/bge-m3`.
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+ - Reranker Name: such as `bge-reranker-v2-m3`. Keep empty for `NoReranker`.
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+ - Reranker URL: such as `https://huggingface.co/BAAI/bge-reranker-v2-m3`. Keep empty for `NoReranker`.
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+
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+ If you want to stay anonymous, you can only fill in the Model Name and Reranker Name (keep empty for `NoReranker`), and check the selection box below befor submission.
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+
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  5. Congratulation! Your results will be shown on the leaderboard in up to one hour.
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  """
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