BioSheildGAP Transformers Models
Contents:
- detector/* checkpoints for sequence classification
- generator/* checkpoint for causal language model
- seqgan/seqgan.pt
Detector example:
from transformers import AutoTokenizer, AutoModelForSequenceClassification
repo_id = "Rayudu25/BioSheildGAP-Transformers-Models"
subfolder = "detector/condition_A"
tokenizer = AutoTokenizer.from_pretrained(repo_id, subfolder=subfolder)
model = AutoModelForSequenceClassification.from_pretrained(repo_id, subfolder=subfolder)
Generator example:
from transformers import AutoTokenizer, AutoModelForCausalLM
repo_id = "Rayudu25/BioSheildGAP-Transformers-Models"
subfolder = "generator"
tokenizer = AutoTokenizer.from_pretrained(repo_id, subfolder=subfolder)
model = AutoModelForCausalLM.from_pretrained(repo_id, subfolder=subfolder)
