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w2v-bert-2.0_SV

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This PR adds a comprehensive model card for the w2v-BERT 2.0 based Speaker Verification model, as described in the paper Enhancing Speaker Verification with w2v-BERT 2.0 and Knowledge Distillation guided Structured Pruning.

The updates include:

• Adding the pipeline_tag: audio-classification for better discoverability of speaker verification models on the Hub.
• Specifying the license: mit.
• Including an additional speaker-verification tag.
• Linking to the academic paper and the official GitHub repository.
• Incorporating the paper's abstract for a quick overview.
• Adding key diagrams and performance tables directly from the GitHub README.
• Providing a BibTeX citation for the paper.

As per instructions, no direct Python usage snippet is included since the GitHub README only provides shell commands and refers to scripts, not a readily copy-pasteable inference snippet for a Hugging Face library.

Please review and merge if these improvements align with expectations.