python pipeline_track_a.py # 完整跑(CKIP+stanza+SBERT+DistilBERT) python pipeline_track_a.py --from-cache # 跳過 CKIP+stanza,直接從 cache/eval_cache.json python pipeline_track_a.py --save-cache # 額外存 D4 pairs ...
Abstract: While user-oriented service industries are rapidly growing, various network devices provide these services through different access paths. Accordingly, the network flow is also increasing ...
A production-quality NLP pipeline that fine-tunes DistilBERT on the Stanford Sentiment Treebank (SST-2) dataset and benchmarks it against two classical baselines — Logistic Regression and LinearSVC — ...
Abstract: This research presents a novel Deep Learning-based framework for evaluating movie theatres within a specific locality by integrating sentiment analysis of user reviews with environmental ...
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