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emb_crossenc_msmarco_miniLM
nishantyadav/emb_crossenc_msmarco_miniLM
emb_crossenc_msmarco_miniLM is a text classification model from nishantyadav. Use it when you need a label for a piece of text. It is set up for transformers.
This is a cross-encoder model with dot-product based scoring mechanism trained on MS-MARCO dataset. The parameters of the cross-encoder are initialized using a 6-layer minilm model and is trained via distillation usin…
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Feb 19, 2024
- Updated
- Feb 19, 2024
- SHA
- 3a5f1db6
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Model card
From the Hugging Face model README
This is a cross-encoder model with dot-product based scoring mechanism trained on MS-MARCO dataset. The parameters of the cross-encoder are initialized using a 6-layer minilm model and is trained via distillation using scores from three different teacher models -- model 1, model 2, and model 3. This model is used in experiments of our EMNLP 2023 and ICLR 2024 papers.
See our EMNLP 2022 paper titled "Efficient Nearest Neighbor Search for Cross-Encoder Models using Matrix Factorization" for more details on the dot-product based scoring mechanism.
license: apache-2.0
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Feb 19, 2024
- Updated
- Feb 19, 2024