フレッシュ スペース & テクノロジー NEWS📢
[Submitted on 2 Sep 2022 (v1), last revised 2 Mar 2023 (this version, v2)] Download PDF Abstract: Many NLP tasks benefit from using large language models (LLMs) that often have more than 100 billion parameters. With the release of BLOOM-176B and OPT-175B, everyone can download pretrained models of this scale. Still, using these models requires…
High-tail 100B language models at house, BitTorrent-style. Soft-tuning and inference as much as 10x faster than offloading Generate textual shriek material the use of disbursed BLOOM and gorgeous-tune it for your like responsibilities: from petals import DistributedBloomForCausalLM model = DistributedBloomForCausalLM.from_pretrained(“bigscience/bloom-petals”, tuning_mode=”ptune”, pre_seq_len=16) # Embeddings & prompts are on your instrument, BLOOM blocks are disbursed all…
