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RaphaelMourad/ModernBERT-DNA-v1-37M-Athaliana
ModernBERT-DNA-v1-37M-Athaliana is a machine learning model from RaphaelMourad. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
The ModernBERT-DNA-v1-37M-Athaliana Large Language Model (LLM) is a pretrained generative DNA sequence model with 37M parameters. It is derived from ModernBERT model, which was simplified for DNA: the number of layers…
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From the Hugging Face model README
The ModernBERT-DNA-v1-37M-Athaliana Large Language Model (LLM) is a pretrained generative DNA sequence model with 37M parameters. It is derived from ModernBERT model, which was simplified for DNA: the number of layers and the hidden size were reduced. The model was pretrained using 10kb DNA sequences from 7 A. thaliana genome assemblies (from https://1001genomes.org/data/MPIPZ/MPIPZJiao2020/releases/current/full_set/).
import torch
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("RaphaelMourad/MModernBERT-DNA-v1-37M-Athaliana", trust_remote_code=True)
model = AutoModel.from_pretrained("RaphaelMourad/ModernBERT-DNA-v1-37M-Athaliana", trust_remote_code=True)
dna = "TGATGATTGGCGCGGCTAGGATCGGCT"
inputs = tokenizer(dna, return_tensors = 'pt')["input_ids"]
hidden_states = model(inputs)[0] # [1, sequence_length, 256]
# embedding with max pooling
embedding_max = torch.max(hidden_states[0], dim=0)[0]
print(embedding_max.shape) # expect to be 256
Ensure you are utilizing a stable version of Transformers, 4.34.0 or newer.
ModernBERT-DNA-v1-37M-Athaliana is a pretrained base model for DNA.
Raphaël Mourad. [email protected]