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@xenova I managed to use the ONNX model from huggingface with a few minor tweaks, but I don't know how you would like to handle them:
The model config.json needs the "model_type": "xlm-roberta" property, otherwise its type is not properly detected by transformers.js
The model_inputs during model execution need a 3rd parameter which is the task_id index from the lora_adaptations list ("retrieval.query", "retrieval.passage", "separation", "classification", "text-matching")
The output results property is "text_embeds", which needs to be added to the relevant inspection list.
1/3 are easy, but for 2 I suppose we need to create special classes/parameters.
Also, there is the Matryoska embeddings thing; does this imply mere dimension clamping of the results or is it something more than that that needs special handling?
Model description
Support for jina-embeddings-v3
Prerequisites
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