This model is to reproduce Contextualized Query Embeddings for Conversational Search described in the following paper:

> Sheng-Chieh Lin, Jheng-Hong Yang, and Jimmy Lin. [Contextualized Query Embeddings for Conversational Search.](https://cs.uwaterloo.ca/~jimmylin/publications/Lin_etal_EMNLP2021.pdf) EMNLP, Nov 2021. 

This model is finetuend only on query ecoder with frezzed passage encoder. The starting point is the [tct_colbert-msmarco](https://huggingface.co/castorini/tct_colbert-msmarco/tree/main). The detailed usage of the model will be out soon on [Chatty Goose](https://github.com/castorini/chatty-goose). You can also check the fine-tuning and inference using tensorflow in our [CQE repo](https://github.com/castorini/CQE)
{}
transformers pytorch bert feature-extraction endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #feature-extraction #endpoints_compatible #region-us 

This model is to reproduce Contextualized Query Embeddings for Conversational Search described in the following paper:

> Sheng-Chieh Lin, Jheng-Hong Yang, and Jimmy Lin. Contextualized Query Embeddings for Conversational Search. EMNLP, Nov 2021. 

This model is finetuend only on query ecoder with frezzed passage encoder. The starting point is the tct_colbert-msmarco. The detailed usage of the model will be out soon on Chatty Goose. You can also check the fine-tuning and inference using tensorflow in our CQE repo
TAGS
#transformers #pytorch #bert #feature-extraction #endpoints_compatible #region-us 

passage: TAGS
#transformers #pytorch #bert #feature-extraction #endpoints_compatible #region-us 
