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The Israel Jewish Spiritual Care Network (IJSCN) recognizes the grave danger inherent in neglecting to establish clear entry-level criteria, training guidelines and credentialing standards for this field, particularly when many people who seek these services are vulnerable prey for charlatans and incompetent \"practitioners.\" The article rightly proffered the concerns of trained psychologists in challenging the aptitude and skill set of current spiritual care providers in tending to complex psychosocial issues and raised the obvious question of how the services of spiritual care providers are distinct from other support personnel. But [Peggy Cidor] failed to provide satisfying responses to these justified queries.

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License.