Edit model card

Model Card for Mistral-DNA-v1-17M-hg38 (Mistral for DNA)

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 DNA: the number of layers and the hidden size were reduced. The model was pretrained using 10kb DNA sequences from the hg38 human genome assembly.

Model Architecture

Like Mixtral-8x7B-v0.1, it is a transformer model, with the following architecture choices:

  • Grouped-Query Attention
  • Sliding-Window Attention
  • Byte-fallback BPE tokenizer
  • Mixture of Experts

Load the model from huggingface:

import torch
from transformers import AutoTokenizer, AutoModel

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 = "TGATGATTGGCGCGGCTAGGATCGGCT"
inputs = tokenizer(insulin, 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

Mistral-DNA-v1-17M-hg38 is a pretrained base model for DNA.

Contact

Raphaël Mourad. [email protected]

Downloads last month
59
Safetensors
Model size
16.8M params
Tensor type
BF16
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.