Bugfix: wrong attention mask calculation resulted in wrong embeddings

[maziyarpanahi]

This pull request includes several updates to the attention mask logic across multiple classes in the com.johnsnowlabs.ml.ai package. The changes primarily involve modifying the condition used to set the attention mask values.

Updates to attention mask logic:

• BGE.scala: Changed the condition for setting attention mask values from x < 0L to x == 0L in both getSentenceEmbeddingFromOv and getSentenceEmbeddingFromOnnx methods. [1] [2]
• E5.scala: Updated the attention mask condition from x < 0L to x == 0L in the getSentenceEmbeddingFromOnnx method. [1] [2]
• MPNet.scala: Modified the attention mask condition from x < this.paddingTokenId to x == this.paddingTokenId in the getSentenceEmbeddingFromOv and getSentenceEmbeddingFromOnnx methods. [1] [2]
• Mxbai.scala: Changed the attention mask condition from x < 0L to x == 0L in the getSentenceEmbeddingFromOnnx method.
• Nomic.scala: Updated the attention mask condition from x < 0L to x == 0L in the getSentenceEmbeddingFromOnnx method. [1] [2]
• SnowFlake.scala: Modified the attention mask condition from x < 0L to x == 0L in both getSentenceEmbeddingFromOv and getSentenceEmbeddingFromOnnx methods. [1] [2]
• UAE.scala: Changed the attention mask condition from x < 0L to x == 0L in both getSentenceEmbeddingFromOpenvino and getSentenceEmbeddingFromOnnx methods. [1] [2] [3]

[ahmedlone127]

LGTM!