Up tókànItọsọna atẹle
Awọn awoṣe Skild AI Robot Foundation
Awọn ile-iṣẹ
Awọn ile-iṣẹ Itọsọna
Snowflake Arctic is a language model released by Snowflake AI Research for enterprise-oriented tasks such as SQL generation, coding, and instruction following.
Gbọ si itọsọna yiiAI-ṣe afihan · ~2 min
Snowflake describes its architecture, weights, and training budget in its release materials; benchmark and cost statements should be read as the company’s reported results under its stated setup.
Snowflake announced Arctic in April 2024. The company describes it as a Dense-MoE Hybrid transformer with 480 billion total parameters and about 17 billion active per token, using top-2 gating across fine-grained experts. Snowflake released base and instruct-tuned checkpoints under Apache 2.0 and reported a training compute budget of roughly under $2 million; this is the company’s estimate and should not be treated as a directly comparable cost for every model. Arctic targets enterprise use cases such as SQL generation, coding, and instruction following. Snowflake also released Arctic Embed models for text embeddings in search and retrieval workflows.
Ṣiṣẹda awọn ibeere SQL ti o pe lati awọn ibeere Gẹẹsi-Gẹẹsi lori ibi ipamọ data ti ile-iṣẹ kan
Ṣiṣe awọn oluranlọwọ koodu-iran ile-iṣẹ agbara laarin iṣẹ Cortex Snowflake
Lilo awọn awoṣe Arctic Embed lati ṣe ilọsiwaju wiwa iwe ati iran imupadabọ
Ṣiṣe ṣiṣi, awoṣe ti a fun ni iwe-aṣẹ Apache lori ile tabi ni awọsanma ikọkọ lati tọju data ifura
The Arctic release illustrates one approach to enterprise language models: publish weights and training details, specialize evaluation for SQL and coding, and provide separate embedding models for retrieval. Model comparisons should identify the checkpoint, benchmark, compute assumptions, and license. Snowflake’s claims about performance and cost describe its own evaluations and disclosures.
Ìwé ìròyìn ọfẹ
Ìtàn AI mẹta tó jẹ́rìí ní gbogbo owurọ́ ọjọ́ iṣẹ́, kọ́wé ní Gẹ̀ẹ́sì tó rọrùn. Ọfẹ́ fún gbogbo àkókò, kò sí ìpolówó.
Ìmeèlì kan ní gbogbo ọjọ́ iṣẹ́. Yọkúrò ní ìkànìyàn ní ìkànìyàn kan. A kò ta tàbí pín àdírẹ́sì rẹ.
Ṣe idanwo fun ara rẹ
Ìdáhùn lẹ́sẹ̀kẹsẹ̀ lórí gbogbo ìdáhùn, àti iwe-ẹ̀rí tó lè pin pẹ̀lú ID tó lè jẹ́rìí lẹ́yìn tí o bá kọ́ ẹ̀kọ́.
Ṣe àtìlẹ́yìn ẹ̀kọ́ AI ọfẹ́. AI Understanding jẹ́ àjọ àìní èrè 501(c)(3) — kò sí ìpolówó, kò sí àkúnya owó, ní gbogbo àkókò. Ṣe ẹbun kan
Snowflake Arctic is a language model released by Snowflake AI Research for enterprise-oriented tasks such as SQL generation, coding, and instruction following. Snowflake describes its architecture, weights, and training budget in its release materials; benchmark and cost statements should be read as the company’s reported results under its stated setup.
Snowflake, ti a mọ fun ile-itaja data awọsanma rẹ, kọ Arctic lati mu AI sunmọ data ile-iṣẹ.
Snowflake reports Arctic has 480B total parameters and uses top-2 gating to activate about 17B per token; these are company-reported architecture figures.
Arctic fojusi 'imọye ile-iṣẹ' gẹgẹbi SQL, koodu, ati itọnisọna ti o tẹle kuku ju iwiregbe ti o ṣii.
Snowflake’s release materials state that Arctic model weights were released under Apache 2.0.
Snowflake reported a training compute budget of roughly under $2 million; this company estimate depends on its accounting and is not automatically comparable across models.
Tesiwaju kikọ
Awọn itọsọna diẹ sii ti a yan fun koko yii
Up tókànItọsọna atẹle
Awọn awoṣe Skild AI Robot Foundation
Awọn ile-iṣẹ