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pro vyhledávání: '"Nussbaum, Zach"'
This technical report describes the training of nomic-embed-vision, a highly performant, open-code, open-weights image embedding model that shares the same latent space as nomic-embed-text. Together, nomic-embed-vision and nomic-embed-text form the f
Externí odkaz:
http://arxiv.org/abs/2406.18587
This technical report describes the training of nomic-embed-text-v1, the first fully reproducible, open-source, open-weights, open-data, 8192 context length English text embedding model that outperforms both OpenAI Ada-002 and OpenAI text-embedding-3
Externí odkaz:
http://arxiv.org/abs/2402.01613
Autor:
Anand, Yuvanesh, Nussbaum, Zach, Treat, Adam, Miller, Aaron, Guo, Richard, Schmidt, Ben, Community, GPT4All, Duderstadt, Brandon, Mulyar, Andriy
Large language models (LLMs) have recently achieved human-level performance on a range of professional and academic benchmarks. The accessibility of these models has lagged behind their performance. State-of-the-art LLMs require costly infrastructure
Externí odkaz:
http://arxiv.org/abs/2311.04931
As machine learning models are increasingly employed to assist human decision-makers, it becomes critical to communicate the uncertainty associated with these model predictions. However, the majority of work on uncertainty has focused on traditional
Externí odkaz:
http://arxiv.org/abs/2107.13098
Autor:
DaSilva LF; Department of Pathology, Harvard Medical School, Boston, MA, USA.; Molecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA., Senan S; Molecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA.; Broad Institute of Harvard and MIT, Cambridge, MA, USA., Patel ZM; Department of Pathology, Harvard Medical School, Boston, MA, USA.; Molecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA.; Broad Institute of Harvard and MIT, Cambridge, MA, USA., Janardhan Reddy A; Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA., Gabbita S; Molecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA.; Johns Hopkins University, Baltimore, MD, USA., Nussbaum Z; Nomic AI., Valdez Córdova CM; Johannes Kepler University, Linz, Austria., Wenteler A; Queen Mary University of London, London, UK., Weber N; TU Vienna, Austria., Tunjic TM; TU Vienna, Austria., Ahmad Khan T; Independent Researcher., Li Z; Victor Chang Cardiac Institute, Darlinghurst, New South Wales, Australia.; School of Biotechnology and Biomolecular Sciences, Faculty of Science, UNSW Sydney, Sydney, Australia., Smith C; Department of Pathology, Harvard Medical School, Boston, MA, USA.; Molecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA.; Broad Institute of Harvard and MIT, Cambridge, MA, USA., Bejan M; University of Bucharest, Bucharest, Romania., Karmel Louis L; Victor Chang Cardiac Institute, Darlinghurst, New South Wales, Australia.; School of Biotechnology and Biomolecular Sciences, Faculty of Science, UNSW Sydney, Sydney, Australia., Cornejo P; Victor Chang Cardiac Institute, Darlinghurst, New South Wales, Australia.; School of Biotechnology and Biomolecular Sciences, Faculty of Science, UNSW Sydney, Sydney, Australia., Connell W; Independent Researcher., Wong ES; Victor Chang Cardiac Institute, Darlinghurst, New South Wales, Australia.; School of Biotechnology and Biomolecular Sciences, Faculty of Science, UNSW Sydney, Sydney, Australia., Meuleman W; Altius Institute for Biomedical Sciences, Seattle, WA, USA.; Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA, USA., Pinello L; Department of Pathology, Harvard Medical School, Boston, MA, USA.; Molecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA.; Broad Institute of Harvard and MIT, Cambridge, MA, USA.
Publikováno v:
BioRxiv : the preprint server for biology [bioRxiv] 2024 Feb 01. Date of Electronic Publication: 2024 Feb 01.