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How can I build a RAG with a model other than Open AI, Cohere and Sagemaker.
Can i use hugging face transformer or BERT model for predicting sentences? without having any hugging face key
i am using version 2.10
If yes how to build a http connector for it? or how can i load the model
I tried this below one.
Can i upload model which seq2se2 and does not require http connector of any keys. Basically i do not want to use the API keys or but the product until i am sure this solutions works out
That's a good question, and I'm not sure I have an answer for you. I'm of the opinion that the resources for running OpenSearch and for running LLMs should be separated - also I don't think that ML-Commons supports running seq2seq natively. So I'm pretty sure you need to host the model externally and connect via the Connector interface.
It might be worth checking out something like torchserve or other open source model hosting places?
As far as building connectors goes, it looks like basically what you need to do is tell opensearch how to construct the http request. So to hit the basic example from the torchserve readme I would expect to be able to do something like
yes above one helped me to create the connector and i have deployed the model as well. Thanks for the guidance
But currently i am stuck with the below issue, i am seeking help from forum of ml
How can I build a RAG with a model other than Open AI, Cohere and Sagemaker.
Can i use hugging face transformer or BERT model for predicting sentences? without having any hugging face key
i am using version 2.10
If yes how to build a http connector for it? or how can i load the model
I tried this below one.
Can i upload model which seq2se2 and does not require http connector of any keys. Basically i do not want to use the API keys or but the product until i am sure this solutions works out
POST /_plugins/_ml/models/_upload
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