"""Auto-generated list of HAKARI-Bench leaderboard Hugging Face models.

This file is not imported by the Space app. It is kept in the Space repo so
Hugging Face can statically link the Space from the listed model repositories.
"""

MODEL_NAMES = [
    "Alibaba-NLP/gte-multilingual-base",
    "Alibaba-NLP/gte-multilingual-reranker-base",
    "answerdotai/answerai-colbert-small-v1",
    "BAAI/bge-m3",
    "BAAI/bge-reranker-v2-m3",
    "BAAI/bge-small-en-v1.5",
    "cl-nagoya/ruri-v3-30m",
    "cl-nagoya/ruri-v3-310m",
    "cl-nagoya/ruri-v3-reranker-310m",
    "codefuse-ai/F2LLM-v2-160M",
    "codefuse-ai/F2LLM-v2-330M",
    "codefuse-ai/F2LLM-v2-80M",
    "colbert-ir/colbertv2.0",
    "cross-encoder/ettin-reranker-150m-v1",
    "cross-encoder/ettin-reranker-17m-v1",
    "cross-encoder/ettin-reranker-32m-v1",
    "cross-encoder/ettin-reranker-400m-v1",
    "cross-encoder/ettin-reranker-68m-v1",
    "cross-encoder/mmarco-mMiniLMv2-L12-H384-v1",
    "google/embeddinggemma-300m",
    "HIT-TMG/KaLM-embedding-multilingual-mini-v1",
    "hotchpotch/bekko-embedding-v1-a25m",
    "hotchpotch/bekko-embedding-v1-a8m",
    "hotchpotch/japanese-reranker-xsmall-v2",
    "hotchpotch/japanese-splade-v2",
    "ibm-granite/granite-embedding-107m-multilingual",
    "ibm-granite/granite-embedding-278m-multilingual",
    "ibm-granite/granite-embedding-30m-sparse",
    "ibm-granite/granite-embedding-311m-multilingual-r2",
    "ibm-granite/granite-embedding-97m-multilingual-r2",
    "intfloat/e5-base-v2",
    "intfloat/e5-large-v2",
    "intfloat/e5-small-v2",
    "intfloat/multilingual-e5-base",
    "intfloat/multilingual-e5-large",
    "intfloat/multilingual-e5-small",
    "jinaai/jina-colbert-v2",
    "jinaai/jina-embeddings-v3",
    "jinaai/jina-embeddings-v5-text-nano",
    "jinaai/jina-embeddings-v5-text-small",
    "jinaai/jina-reranker-v2-base-multilingual",
    "KaLM-Embedding/KaLM-embedding-multilingual-mini-instruct-v2.5",
    "Lajavaness/bilingual-embedding-base",
    "Lajavaness/bilingual-embedding-small",
    "lightonai/ColBERT-Zero",
    "lightonai/DenseOn",
    "lightonai/GTE-ModernColBERT-v1",
    "lightonai/LateOn",
    "lightonai/mDenseOn",
    "lightonai/mLateOn",
    "LiquidAI/LFM2.5-ColBERT-350M",
    "LiquidAI/LFM2.5-Embedding-350M",
    "microsoft/harrier-oss-v1-0.6b",
    "microsoft/harrier-oss-v1-270m",
    "mixedbread-ai/mxbai-edge-colbert-v0-17m",
    "mixedbread-ai/mxbai-edge-colbert-v0-32m",
    "mixedbread-ai/mxbai-embed-xsmall-v1",
    "mixedbread-ai/mxbai-rerank-base-v2",
    "naver/splade-v3",
    "nomic-ai/nomic-embed-text-v1.5",
    "nomic-ai/nomic-embed-text-v2-moe",
    "nvidia/Nemotron-3-Embed-1B-BF16",
    "nvidia/Nemotron-3-Embed-8B-BF16",
    "opensearch-project/opensearch-neural-sparse-encoding-multilingual-v1",
    "perplexity-ai/pplx-embed-v1-0.6b",
    "perplexity-ai/pplx-embed-v1-4B",
    "perplexity-ai/pplx-embed-v1-late-0.6b",
    "prithivida/Splade_PP_en_v2",
    "Qwen/Qwen3-Embedding-0.6B",
    "Qwen/Qwen3-Embedding-4B",
    "Qwen/Qwen3-Embedding-8B",
    "Qwen/Qwen3-Reranker-0.6B",
    "sbintuitions/sarashina-embedding-v2-1b",
    "sentence-transformers/all-MiniLM-L12-v2",
    "sentence-transformers/all-MiniLM-L6-v2",
    "sentence-transformers/all-mpnet-base-v2",
    "sentence-transformers/LaBSE",
    "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2",
    "sentence-transformers/paraphrase-multilingual-mpnet-base-v2",
    "sentence-transformers/static-similarity-mrl-multilingual-v1",
    "Snowflake/snowflake-arctic-embed-l-v2.0",
    "voyageai/voyage-4-nano",
]