Update README.md

README.md

@@ -38,7 +38,7 @@ Here is a simple code for inference:
 ```python
 from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
 
-model_name = 'agront-1b-promoter_strength_leaf'
+model_name = 'agront-1b-promoter_strength_protoplast'
 # load model and tokenizer
 model = AutoModelForSequenceClassification.from_pretrained(f'zhangtaolab/{model_name}', trust_remote_code=True)
 tokenizer = AutoTokenizer.from_pretrained(f'zhangtaolab/{model_name}', trust_remote_code=True)
@@ -47,7 +47,7 @@ tokenizer = AutoTokenizer.from_pretrained(f'zhangtaolab/{model_name}', trust_rem
 sequences = ['TACTCTAATCGTATCAGCTGCACTTGCGTACAGGCTACCGGCGTCCTCAGCCACGTAAGAAAAGGCCCAATAAAGGCCCAACTACAACCAGCGGATATATATACTGGAGCCTGGCGAGATCACCCTAACCCCTCACACTCCCATCCAGCCGCCACCAGGTGCAGAGTGTT',
              'ATTTCAAAACTAGTTTTCTATAAACGAAAACTTATATTTATTCCGCTTGTTCCGTTTGATCTGCTGATTCGACACCGTTTTAACGTATTTTAAGTAAGTATCAGAAATATTAATGTGAAGATAAAAGAAAATAGAGTAAATGTAAAGGAAAATGCATAAGATTTTGTTGA']
 pipe = pipeline('text-classification', model=model, tokenizer=tokenizer,
-                trust_remote_code=True, top_k=None)
+                trust_remote_code=True, function_to_apply="none")
 results = pipe(sequences)
 print(results)