Update README.md

README.md

@@ -6,11 +6,11 @@ tags:
 - protein
 ---
 
-# Model Card for Mistral-Prot-v1-15M (Mistral for protein)
+# Model Card for Mistral-DNA-v1-17M-hg38 (Mistral for protein)
 
-The Mistral-Prot-v1-15M Large Language Model (LLM) is a pretrained generative protein molecule model with 15.2M parameters. 
+The Mistral-DNA-v1-17M-hg38 Large Language Model (LLM) is a pretrained generative DNA sequence model with 16.8M parameters. 
 It is derived from Mixtral-8x7B-v0.1 model, which was simplified for protein: the number of layers and the hidden size were reduced. 
-The model was pretrained using 1M protein strings from the uniprot 50 database. 
+The model was pretrained using 10kb DNA sequences from the hg38 human genome assembly. 
 
 ## Model Architecture
 
@@ -26,14 +26,14 @@ Like Mixtral-8x7B-v0.1, it is a transformer model, with the following architectu
 import torch
 from transformers import AutoTokenizer, AutoModel
 
-tokenizer = AutoTokenizer.from_pretrained("RaphaelMourad/Mistral-Prot-v1-15M", trust_remote_code=True) 
-model = AutoModel.from_pretrained("RaphaelMourad/Mistral-Prot-v1-15M", trust_remote_code=True)
+tokenizer = AutoTokenizer.from_pretrained("RaphaelMourad/Mistral-DNA-v1-17M-hg38", trust_remote_code=True) 
+model = AutoModel.from_pretrained("RaphaelMourad/Mistral-DNA-v1-17M-hg38", trust_remote_code=True)
 ```
 
 ## Calculate the embedding of a protein sequence
 
 ```
-insulin = "MALWMRLLPLLALLALWGPDPAAAFVNQHLCGSHLVEALYLVCGERGFFYTPKTRREAEDLQVGQVELGGGPGAGSLQPLALEGSLQKRGIVEQCCTSICSLYQLENYCN"
+insulin = "TGATGATTGGCGCGGCTAGGATCGGCT"
 inputs = tokenizer(insulin, return_tensors = 'pt')["input_ids"]
 hidden_states = model(inputs)[0] # [1, sequence_length, 256]
 
@@ -48,7 +48,7 @@ Ensure you are utilizing a stable version of Transformers, 4.34.0 or newer.
 
 ## Notice
 
-Mistral-Prot-v1-15M is a pretrained base model for protein.
+Mistral-DNA-v1-17M-hg38 is a pretrained base model for DNA.
 
 ## Contact