Update app.py

app.py

@@ -2,22 +2,25 @@ import gradio
 from transformers import GPT2LMHeadModel, GPT2Tokenizer, AdamW
 from transformers import AutoTokenizer, AutoModelForCausalLM
 
-#from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
 
 
 
-model_name = "zaanind/nllb-ensi-v1-srtgen" #"zaanind/nllb-ensi-v1-tuning-subs"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
 
-tokenizer.src_lang = "eng_Latn"
+model_name = "zaanind/gpt2_finetune_alpaca"
+
+
+tokenizer = GPT2Tokenizer.from_pretrained(model_name)
+tokenizer.pad_token = tokenizer.eos_token
+
+model = GPT2LMHeadModel.from_pretrained(model_name)
+
+
 
 def translate(text):
-    inputs = tokenizer(text=text, return_tensors="pt")
-    translated_tokens = model.generate(
-        **inputs, forced_bos_token_id=tokenizer.lang_code_to_id["sin_Sinh"]
-    )
-    translation = tokenizer.decode(translated_tokens[0], skip_special_tokens=True)
+    prompt = f"<s>[INST] translate this sentence to sinhala - {text} [/INST] sure,here the translation of the provided text - "
+    input_ids = tokenizer.encode(prompt, return_tensors='pt')
+    output = model.generate(input_ids, max_length=250, num_return_sequences=1)
+    translation = tokenizer.decode(generated, skip_special_tokens=True)
     return translation
 
     
@@ -29,7 +32,7 @@ gradio_interface = gradio.Interface(
   fn=nmtapifunc,
   inputs="text",
   outputs="text",
-  title="En-Si NMT",
+  title="ZoomAI Inference Server",
   description="",
   article="© zaanind 2024"
 )