initial commint

app.py

@@ -0,0 +1,24 @@
+from transformers import pipeline, AutoModelForMaskedLM, AutoTokenizer
+import gradio as gr
+
+model_name = "kuleshov-group/PlantCaduceus_l20"
+model = AutoModelForMaskedLM.from_pretrained(model_name, trust_remote_code=True)
+tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
+
+nlp = pipeline("fill-mask", model=model, tokenizer=tokenizer)
+
+def predict_masked_text(text):
+    results = nlp(text)
+    return [result['sequence'] for result in results]
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=predict_masked_text,
+    inputs=gr.Textbox(lines=2, placeholder="Enter text with a [MASK] token..."),
+    outputs=gr.Textbox(),
+    title="Masked Language Modeling",
+    description="Fill in the masked token in the input text."
+)
+
+# Launch the interface
+iface.launch(server_port = 8020)

requirements.txt

@@ -0,0 +1,6 @@
+gradio==3.1
+transformers==4.33.3
+torch==2.0.1
+mamba-ssm==1.1.3.post1
+pytorch==2.1.1
+