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fahmiaziz98
commited on
Commit
·
e137aba
1
Parent(s):
313c5a2
change granite to splade pp v1
Browse files- config.yaml +4 -4
config.yaml
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@@ -40,7 +40,7 @@ models:
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language: ["multilingual"]
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repository: "https://huggingface.co/intfloat/multilingual-e5-small"
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splade-v3:
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name: "naver/splade-v3"
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type: "sparse-embeddings"
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dimension: 1234 # must add this field
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@@ -68,8 +68,8 @@ models:
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language: ["multilingual"]
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repository: "https://huggingface.co/prithivida/Splade_PP_en_v2"
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name: "
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type: "sparse-embeddings"
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dimension: 1234 # must add this field
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max_tokens: 1234
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@@ -79,4 +79,4 @@ models:
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enterprise-friendly license, and IBM collected and generated datasets. While maintaining competitive scores on academic benchmarks such as BEIR, this model also performs well on many enterprise use cases.
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This model is developed using retrieval oriented pretraining, contrastive finetuning and knowledge distillation for improved performance.
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language: ["En"]
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repository: "https://huggingface.co/
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language: ["multilingual"]
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repository: "https://huggingface.co/intfloat/multilingual-e5-small"
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naver-splade-v3:
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name: "naver/splade-v3"
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type: "sparse-embeddings"
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dimension: 1234 # must add this field
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language: ["multilingual"]
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repository: "https://huggingface.co/prithivida/Splade_PP_en_v2"
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splade-pp-v1:
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name: "prithivida/Splade_PP_en_v1"
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type: "sparse-embeddings"
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dimension: 1234 # must add this field
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max_tokens: 1234
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enterprise-friendly license, and IBM collected and generated datasets. While maintaining competitive scores on academic benchmarks such as BEIR, this model also performs well on many enterprise use cases.
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This model is developed using retrieval oriented pretraining, contrastive finetuning and knowledge distillation for improved performance.
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language: ["En"]
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repository: "https://huggingface.co/prithivida/Splade_PP_en_v1"
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