agro-nucleotide-transformer-1b

模型介绍

AgroNT is a DNA language model trained on primarily edible plant genomes. More specifically, AgroNT uses the transformer architecture with self-attention and a masked language modeling objective to leverage highly available genotype data from 48 different plant speices to learn general representations of nucleotide sequences. AgroNT contains 1 billion parameters and has a context window of 1024 tokens. AgroNt uses a non-overlapping 6-mer tokenizer to convert genomic nucletoide sequences to tokens. As a result the 1024 tokens correspond to approximately 6144 base pairs. Our pre-training dataset was built from (mostly) edible plants reference genomes contained in the Ensembl Plants database. The dataset consists of approximately 10.5 million genomic sequences across 48 different species. All reference genomes for each specie were assembled into a single fasta file. In this fasta file, all nucleotides other than A, T, C, G were replaced by N. A tokenizer was used to convert strings of letters into sequences of tokens. The tokenizer's alphabet consisted of the 4 6 = 4096 possible 6-mer combinations obtained by combining A, T, C, G, as well as five additional tokens representing standalone A, T, C, G, and N. It also included three special tokens: the pad [PAD], mask [MASK], and class [CLS] tokens. This resulted in a vocabulary of 4104 tokens. To tokenize an input sequence, the tokenizer started with a class token and then converted the sequence from left to right, matching 6-mer tokens when possible, or using the standalone tokens when necessary (for instance, when the letter N was present or if the sequence length was not a multiple of 6).

主要特点

特点摘要待依据来源补齐，不凭模型名称推断能力。

局限与注意事项

暂无足够来源支持具体缺点结论。请重点验证实际任务表现、时延、数据政策、许可与版本生命周期。

来源报价与费用分析

同一模型在不同渠道、地区和配置下可能采用不同价格。下表独立保留各渠道报价，不将渠道价格视为厂商官方统一价格。

公开评测与运行配置

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

常见问题

资料来源与可追溯记录

许可证：cc-by-nc-sa-4.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。