Update README.md

README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+tags:
+- pretrained
+- modernbert
+- DNA
+- virus
+---
+
+# Model Card for ModernBert-DNA-v1-37M-virus (Mistral for DNA)
+
+The ModernBert-DNA-v1-37M-virus 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 around 15071 viruses > 1kb. Virus genomes were split into 1kb sequences.
+
+Virus genome database was downloaded from https://www.ncbi.nlm.nih.gov/labs/virus/vssi/#/virus?SeqType_s=Genome&VirusLineage_ss=taxid:10239&SourceDB_s=RefSeq.
+NB: the DNA sequence was used, not the RNA sequence.  
+
+
+## Load the model from huggingface:
+
+```
+import torch
+from transformers import AutoTokenizer, AutoModel
+
+tokenizer = AutoTokenizer.from_pretrained("RaphaelMourad/ModernBert-DNA-v1-37M-virus", trust_remote_code=True) 
+model = AutoModel.from_pretrained("RaphaelMourad/ModernBert-DNA-v1-37M-virus", trust_remote_code=True)
+```
+
+## Calculate the embedding of a DNA sequence
+
+```
+DNAseq = "TGATGATTGGCGCGGCTAGGATCGGCT"
+inputs = tokenizer(DNAseq, 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
+```
+
+## Troubleshooting
+
+Ensure you are utilizing a stable version of Transformers, 4.34.0 or newer.
+
+## Notice
+
+ModernBert-DNA-v1-37M-virus is a pretrained base model for DNA.
+
+## Contact
+ 
+Raphaël Mourad. [email protected]