Added seaborn and removed auth token

app.py

@@ -82,11 +82,11 @@ def get_mutated_protein(sequence,mutant):
 
 def score_and_create_matrix_all_singles(sequence,mutation_range_start=None,mutation_range_end=None,model_type="Small",scoring_mirror=False,batch_size_inference=20,num_workers=0,AA_vocab=AA_vocab):
   if model_type=="Small":
-    model = tranception.model_pytorch.TranceptionLMHeadModel.from_pretrained(pretrained_model_name_or_path="PascalNotin/Tranception_Small",use_auth_token=True)
+    model = tranception.model_pytorch.TranceptionLMHeadModel.from_pretrained(pretrained_model_name_or_path="PascalNotin/Tranception_Small")
   elif model_type=="Medium":
-    model = tranception.model_pytorch.TranceptionLMHeadModel.from_pretrained(pretrained_model_name_or_path="PascalNotin/Tranception_Medium",use_auth_token=True)
+    model = tranception.model_pytorch.TranceptionLMHeadModel.from_pretrained(pretrained_model_name_or_path="PascalNotin/Tranception_Medium")
   elif model_type=="Large":
-    model = tranception.model_pytorch.TranceptionLMHeadModel.from_pretrained(pretrained_model_name_or_path="PascalNotin/Tranception_Large",use_auth_token=True)
+    model = tranception.model_pytorch.TranceptionLMHeadModel.from_pretrained(pretrained_model_name_or_path="PascalNotin/Tranception_Large")
   model.config.tokenizer = tokenizer
   all_single_mutants = create_all_single_mutants(sequence,AA_vocab,mutation_range_start,mutation_range_end)
   scores = model.score_mutants(DMS_data=all_single_mutants, 

requirements.txt

@@ -2,4 +2,5 @@ gradio
 transformers==4.17
 datasets==1.18.3
 biopython==1.78
-torch
+torch
+seaborn