dna_promoter_sft

brief

DNA sequence and Human Language mixed large language model with fine tuning

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basic use

import torch
from transformers import GPT2Tokenizer,GPT2Model,GPT2LMHeadModel

model = GPT2LMHeadModel.from_pretrained("dnagpt/dna_promoter_sft")
tokenizer = GPT2Tokenizer.from_pretrained("dnagpt/dna_eng_bpe")

input = """
Below is an instruction that describes a task. Write a response that appropriately completes the request.

### Instruction:
Determine the following dna sequence is promoter or terminator

### Input:
TCTTTCTCTTCTGTATCATTCTACTTCTATGACTGCTCCTTCTCGAGTAAAACAGAATGTGTCTCAGGATTACTTTAAAACAAGACAAAGTATAGAGTTAAAATACATTTTTGTTTAGGTAAATATCATCAAATAATCCAATTTGGAAACCAACATTCTTACTTCTTTTTCCAACAGTTGTTCCTATCATCATAAAAACAGAGAGGGTAAGCCTTGGGGAAAGCTACTTTAAAAAAATGGCCTCTAAGGATATTCAGGGTGCAAACAGTAACCTGTTCAGGCACAGATTCTTCTCCTTGAAATGAACTGAAGTTGGCAAATATTCCTCACAGCCTGTTGGAGGGTTCAGCAGTTTATTACAGAAGTATGAAATGCTTTTATTTAAAAAATGTATTTTGGTACACATGTTAGTCTTTTTTGTGATGAACTTCACAGATACATTTGACATTGGTATGCCTCATTTATTTGTTGAAATTTTTTTCTTTGGCTTCCATGAAGTTAAGATTTTTCAAGCAAGATGAAGTCCATCATCCTCTTTGTCCTTTCCCTGCTCCTTATCTTGGAGAAGCAAGCAGCTGTGATGGGACAAAAAGGTGAGTGATGGTTTCAGCTGGACTCCATCCTTCAACTGACAACCCAACACAACTGTATTCATCTCTCGTTAACATTACTAGCAGTGAGTAACATCAGAAAGTTTTTGAGTCTCCTTCCTACTCCGGACTGAATTTCTTCTGTATAATGCAAGCGATCTGGCATGATGATATACAAAGACCGATAAAATTTTGCTGGGGATTCTGAAAGTAAAAAAAATTGCCTTTGATATTATGTCCCCATGCTAAGTCCCTGGGGACTTTGACATTATCCCCCACTGAGCAGGGGTGAGGAAGCTGGCATTTACTAAAAAGTCAGCAATATGATTTGAATGCCCTACATAAGGCGACAAAATCAAAACAACACCTAGGTGGAAGTCAACAACTGCTCAATTATAAACAAGAAGGCAATAAGCTATGAAAGGGCAGTGCCTTTTGACATTTCAGCTCCACCCATAGCACACCCACTCAAGGAACATATAAATGAAGAGATCCGCTCAGTTCTCAGACCTATTTTGGACAAAAAGACCAACAACATACTAAATCCAAAGGCAGTTTTTCTATTCAACACACATATCATGTAGACATCAATGATCATGACTGGACCCGATGAGAATTGATTTTTCTCCACCCAACGCTGTAGGCTTTTGGAAATATCAGAAATTTGTTGGGAAAAGGTGGGAGGTAAGAGTTGCAAGAGAGCTTTGGAGATAATGAATGCATACATTTCTATTATCAATTACCAGGTGGATCAAAAGGCCAATTGCCAAGCGGATCTTCCCAATTTCCACATGGACAAAAGGGCCAGCATACCTAAAATTTAGTATTTAAGTTATTGGATCAGAAAGGAAACTCGCATTTAGAGTATGAAGGCATTGTCAGCCACCAATTACTTTTGTAACCTGAAGCTGAATAGCCCATCTGGAAAGGGATTATCCAGTCAATGTTCAAACACAGAAAAAAGGCTATGGGTTCATGGACTAAGTAAAGAACAAGCTTCAGCCTCTGGTGAGACCATGATAAATCAAAAGGTCATTTTCACATGATAGTTATACATCATAAAGGAGGCCAAGCTCATCATGGGACACAAAATCCTTCTCAAGATCAGGGTGTTAAATTTTTCTCATCCTTTCAAAAAATCTCTGGAGCTTACCTCACCCTCCAGATACAGCCTCACCTCTCATTCCACCATGAAATCAGACTTCTTGAGGCACAAAAAGGTAGAACACAAGGTGGATCCCAAAGCAGTTATGTTCTCCAAACTGAAGAACTAGTAGTTAACAAACAACAACGTGAGACTAAAAATTCTCATCAAAATAAAGGGCATTACCAAAATGTGGTTGACGTGAGAGAGGAACATTCAAGTAAACTACAAACTTCACTCCATCCTGCACATCAAGACAGACTCCA

### Response:
"""

input_ids = tokenizer.encode(
      input,
      return_tensors="pt",
      truncation=True,
      max_length=1000
)

# Generate
device = model.device

generated_tokens_with_prompt = model.generate(
input_ids=input_ids.to(device),
max_new_tokens=3,
)

generated_text_with_prompt = tokenizer.decode(generated_tokens_with_prompt[0], skip_special_tokens=True)
generated_text_answer = generated_text_with_prompt[len(input):]

print(generated_text_answer)

#terminator

github

https://github.com/maris205/DNAHL