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@@ -11,7 +11,7 @@ tags:
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  - plants
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  ---
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  ## Model Overview
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- 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
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  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.
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  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.
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@@ -22,7 +22,7 @@ from transformers import AutoModelForMaskedLM, AutoTokenizer
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  import torch
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- model_name = 'agro-nt'
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  # fetch model and tokenizer from InstaDeep's hf repo
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  agro_nt_model = AutoModelForMaskedLM.from_pretrained(f'InstaDeepAI/{model_name}')
 
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  - plants
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  ---
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  ## Model Overview
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+ 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
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  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.
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  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.
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  import torch
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+ model_name = 'agro-nucleotide-transformer-1b'
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  # fetch model and tokenizer from InstaDeep's hf repo
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  agro_nt_model = AutoModelForMaskedLM.from_pretrained(f'InstaDeepAI/{model_name}')