Create app.py

app.py

@@ -0,0 +1,35 @@
+import gradio as gr
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+import torch
+
+title = "Protien Sequence Classification 🧬."
+description = "Predicts the subcellular location of the protein sequence between two classes: Cytoplasm and Membrane"
+article = 'Created from finetuning ESM2_150M'
+
+model = AutoModelForSequenceClassification.from_pretrained('./Model')
+tokenizer = AutoTokenizer.from_pretrained('facebook/esm2_t30_150M_UR50D')
+
+example_list = [['MKIIILLGFLGATLSAPLIPQRLMSASNSNELLLNLNNGQLLPLQLQGPLNSWIPPFSGILQQQQQAQIPGLSQFSLSALDQFAGLLPNQIPLTGEASFAQGAQAGQVDPLQLQTPPQTQPGPSHVMPYVFSFKMPQEQGQMFQYYPVYMVLPWEQPQQTVPRSPQQTRQQQYEEQIPFYAQFGYIPQLAEPAISGGQQQLAFDPQLGTAPEIAVMSTGEEIPYLQKEAINFRHDSAGVFMPSTSPKPSTTNVFTSAVDQTITPELPEEKDKTDSLREP'],
+ ['MSSGNYQQSEALSKPTFSEEQASALVESVFGLKVSKVRPLPSYDDQNFHVYVSKTKDGPTEYVLKISNTKASKNPDLIEVQNHIIMFLKAAGFPTASVCHTKGDNTASLVSVDSGSEIKSYLVRLLTYLPGRPIAELPVSPQLLYEIGKLAAKLDKTLQRFHHPKLSSLHRENFIWNLKNVPLLEKYLYALGQNRNREIVEHVIHLFKEEVMTKLSHFRECINHGDLNDHNILIESSKSASGNAEYQVSGILDFGDMSYGYYVFEVAITIMYMMIESKSPIQVGGHVLAGFESITPLTAVEKGALFLLVCSRFCQSLVMAAYSCQLYPENKDYLMVTAKTGWKHLQQMFDMGQKAVEEIWFETAKSYESGISM'],
+ ['MMNNTDFLMLNNPWNKLCLVSMDFCFPLDFVSNLFWIFASKFIIVTGQIKADFKRTSWEAKAEGSLEPGRLKLQLASIVPLYSSLVTAGPASKIIILKRTSLPTVSPSNERAYLLPVSFTDLAHVFYLSYFSINAKSNSFSLDIIIALGIPHNTQAHFNH'],
+ ['MNKHNLRLVQLASELILIEIIPKLFLSQVTTISHIKREKIPPNHRKGILCMFPWQCVVYVFSNFVWLVIHRFSNGFIQFLGEPYRLMTASGTHGRIKFMVDIPIIKNTQVLRIPVLKDPKMLSKKH']]
+
+def predict(ProtienSequence):
+    input = tokenizer(ProtienSequence, return_tensors='pt')
+    with torch.inference_mode():
+        outputs = model(**input)
+    output = outputs.logits.argmax(axis=1)[0].numpy() == 0
+    print(output)
+    if output:
+        return str('Cytoplasm')
+    else:
+        return str('Membrane')
+
+iface = gr.Interface(fn=predict,
+                    inputs='text',
+                    outputs=gr.Text(label='Subcellular location'),
+                             title=title,
+                             description=description,
+                             article=article,
+                             examples=example_list)
+iface.launch()