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AI 模型 85003

• gliner_medium_news-v2.1↗

  EmergentMethods

  This model is a fine-tune of GLiNER aimed at improving accuracy across a broad range of topics, especially with respect to long-context news entity extraction. As shown in the table below, these fine-tunes improved upon the base GLiNER model zero-shot accuracy by up to 7.5% across 18 benchmark datasets. The underlying dataset, AskNews-NER-v0 was engineered with the objective of diversifying global perspectives by enforcing country/language/topic/temporal diversity. All data used to fine-tune this model was synthetically generated. WizardLM 13B v1.2 was used for translation/summarization of open-web news articles, while Llama3 70b instruct was used for entity extraction. Both the diversification and fine-tuning methods are presented in a our paper on ArXiv. The synthetic data underlying this news fine-tune was pulled from the AskNews API. We enforced diveristy across country/language/topic/time.

• mms-tts-bqp↗

  facebook

• opt-iml-max-1.3b↗

  facebook

• fim-sde↗

  FIM4Science

• Strand-Rust-Coder-14B-v1↗

  Fortytwo-Network

• eng-100mb-after-wc-from-jpn-uniform-newlex-after-ckpt500-packed-bfdiso_seed455↗

  francesca9805

• GLM-4.5V-GGUF↗

  ggml-org

• madlad400-8b-lm↗

  Google

• multiberts-seed_20↗

  Google

• ViGoRL-7b-Spatial↗

  gsarch