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## v1.1.0
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- Rename EmbeddingGenerator to EmbeddingEncoder
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- - Use non-quantized default model by default for better embedding performance but require more memory
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- Fixed serverOptions weren't passed through properly in test cases
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- Upgrade to @huggingface/transformers v3.2.4
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- Upgrade onnxruntime-node v1.20.1
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+ - Avoid including unused models in docker images (smaller image size)
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+ - Increase probe timeout seconds
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+ - Use worker pool
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+ - Process sentence list with separate model runs
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+ - set default ` workerTaskTimeout ` to ` 60 ` seconds
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+ - use quantized version (q8) default model
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+ - set default ` limits.memory ` to ` 850M `
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+ - set default replicas number to ` 2 `
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+ - Add max_length config to model config (configurable via helm config)
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+ - set max_length of default model to 1024 due to excessive memory usage when working on text longer than 2048 (the default model supports up to 8192)
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+ - only use padding for multiple inputs received when encoding the input
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## v1.0.0
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