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AI モデル 84999

• Dayhoff-170M-UR90-HL-24000↗

  Microsoft

• tapex-base-finetuned-wikisql↗

  Microsoft

  TAPEX was proposed in TAPEX: Table Pre-training via Learning a Neural SQL Executor by Qian Liu, Bei Chen, Jiaqi Guo, Morteza Ziyadi, Zeqi Lin, Weizhu Chen, Jian-Guang Lou. The original repo can be found here. TAPEX (**Ta**ble **P**re-training via **Ex**ecution) is a conceptually simple and empirically powerful pre-training approach to empower existing models with *table reasoning* skills. TAPEX realizes table pre-training by learning a neural SQL executor over a synthetic corpus, which is obtained by automatically synthesizing executable SQL queries. TAPEX is based on the BART architecture, the transformer encoder-encoder (seq2seq) model with a bidirectional (BERT-like) encoder and an autoregressive (GPT-like) decoder.

• unispeech-large-fr-ft↗

  Microsoft

• 5FUMG9qvpoSaNVKvZRUnwVTapie7Lu2NYjevMLpXxJqfmuCM_vgg↗

  minatolegend0311

• MobileMoE-L-QAT↗

  ml-resources

• GUI-Owl-1.5-32B-Instruct↗

  mPLUG

• borealis-open-270m-i1-GGUF↗

  mradermacher

• Chen-9B-GGUF↗

  mradermacher

• danbooruTagAutocomplete-i1-GGUF↗

  mradermacher

• Darwin-28B-Coder-i1-GGUF↗

  mradermacher