fix model name

app.py

@@ -22,7 +22,7 @@ def __run_pipline():
 def __run_model():
     st.text(f"input_text: {state.input_text}")
     st.markdown(":green[Running model]")
-    st.text(model.model(state.input_text))
+    st.text(model.run(state.input_text))
 
 
 st.text_area("input_text", key="input_text")

model.py

@@ -12,7 +12,7 @@ tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype="auto", device_map="auto").to(device=device)
 
 
-def model(text,**kargs):
+def run(text,**kargs):
     inputs = tokenizer.encode(text=text, return_tensors="pt").to(device=device)
     outputs = model.generate(inputs,**kargs)
     return tokenizer.decode(outputs[0])

pipline.py

@@ -2,7 +2,7 @@ import langchain as lc
 from langchain import PromptTemplate
 from langchain.prompts import load_prompt
 import wikipedia
-from model import model
+import model
 
 # save templates to a file
 
@@ -24,7 +24,7 @@ def pipeline(text, word):
     model_output = ""
     input_text = prompt.format(adjective="funny", content=text)
     while word not in model_output:
-        model_output = model(input_text)
+        model_output = model.run(input_text)
         wikipedia_entry = wikipedia.search(word)[1]
         wiki = wikipedia.summary(wikipedia_entry, auto_suggest=False, redirect=True)
         input_text += model_output + wiki