py files

app.py

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+from transformers import T5ForConditionalGeneration, AutoTokenizer
+import gradio as gr
+import os
+cwd = os.getcwd()
+
+print("Starting")
+device = "cpu"
+
+checkpoint = "./models/codet5_large_typescript"
+
+tokenizer = AutoTokenizer.from_pretrained(checkpoint, local_files_only=True)
+
+print("Loading Model")
+model = T5ForConditionalGeneration.from_pretrained(checkpoint, local_files_only=True).to(device)
+print("Model Loaded")
+
+def completeCode(prompt):
+	inputs = tokenizer.encode(prompt, return_tensors="pt").to(device)
+	outputs = model.generate(inputs, max_new_tokens = 100, early_stopping = True ).to(device)
+	return tokenizer.decode(outputs[0])
+
+iface = gr.Interface(fn=completeCode, inputs="text", outputs="text")
+iface.launch()
+print("Ready")

requirements.txt

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+transformers
+torch
+torchvision
+torchaudio