distilbert-onnx
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Model obtained by Fine Tuning 'facebook/bart-large-xsum' using AMI Meeting Corpus, SAMSUM Dataset, DIALOGSUM Dataset, XSUM Dataset!
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**Polyglot-Lion-1.7B: High-accuracy multilingual ASR for Singapore — English, Mandarin, Tamil & Malay** Polyglot-Lion-1.7B was developed by Quy-Anh Dang and Chris Ngo at Knovel Engineering and presented in the report "Polyglot-Lion: Efficient Multilingual ASR for Singapore via Balanced Fine-Tuning of Qwen3-ASR". The model is obtained by fine-tuning Qwen3-ASR-1.7B exclusively on publicly available speech corpora covering Singapore's four official languages. It utilizes a balanced sampling strategy that equalizes the number of training utterances per language and deliberately omits language-tag conditioning, allowing the model to learn to identify languages implicitly from audio.
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This is an efficient zero-shot classifier inspired by GLiNER work. It demonstrates the same performance as a cross-encoder while being more compute-efficient because classification is done at a single forward path. It can be used for `topic classification`, `sentiment analysis`, and as a reranker in `RAG` pipelines. The model was trained on logical tasks to induce reasoning. LoRa adapters were used to fine-tune the model without destroying the previous knowledge.
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