Update app.py

app.py

@@ -34,22 +34,22 @@ print("Dolly Pipeline Loaded!")
 llm_dolly = HuggingFacePipeline(pipeline=instruct_pipeline)
 
 
-print("Loading Pipeline Alpaca...")
-tokenizer_alpaca = LlamaTokenizer.from_pretrained('minlik/chinese-alpaca-plus-7b-merged')
-model_alpaca = LlamaForCausalLM.from_pretrained('minlik/chinese-alpaca-plus-7b-merged')
-instruct_pipeline_alpaca = pipeline(
-    "text-generation",
-    model=model_alpaca,
-    tokenizer=tokenizer_alpaca,
-    max_length=1024,
-    temperature=0.6,
-    pad_token_id=tokenizer_alpaca.eos_token_id,
-    top_p=0.95,
-    repetition_penalty=1.2,
-    device_map= "auto"
-)
-print("Pipeline Loaded Alpaca!")
-llm_alpaca = HuggingFacePipeline(pipeline=instruct_pipeline_alpaca)
+# print("Loading Pipeline Alpaca...")
+# tokenizer_alpaca = LlamaTokenizer.from_pretrained('minlik/chinese-alpaca-plus-7b-merged')
+# model_alpaca = LlamaForCausalLM.from_pretrained('minlik/chinese-alpaca-plus-7b-merged')
+# instruct_pipeline_alpaca = pipeline(
+#     "text-generation",
+#     model=model_alpaca,
+#     tokenizer=tokenizer_alpaca,
+#     max_length=1024,
+#     temperature=0.6,
+#     pad_token_id=tokenizer_alpaca.eos_token_id,
+#     top_p=0.95,
+#     repetition_penalty=1.2,
+#     device_map= "auto"
+# )
+# print("Pipeline Loaded Alpaca!")
+# llm_alpaca = HuggingFacePipeline(pipeline=instruct_pipeline_alpaca)
 
 def summarize(Model, File, Input_text):
     prompt_template = """Write a concise summary of the following:
@@ -80,7 +80,7 @@ def summarize(Model, File, Input_text):
     if Model=='Dolly':
         chain = load_summarize_chain(llm_dolly, chain_type="refine", question_prompt=PROMPT)
     else:
-        chain = load_summarize_chain(llm_alpaca, chain_type="refine", question_prompt=PROMPT)
+        chain = load_summarize_chain(llm_dolly, chain_type="refine", question_prompt=PROMPT)
     summary_text = chain({"input_documents": docs}, return_only_outputs=True)
     print(summary_text["output_text"])
     return summary_text["output_text"]