Why I am getting this problem while running any of the GGUF model instead of with .bin model
from langchain.document_loaders.csv_loader import CSVLoaderfrom langchain.text_splitter import RecursiveCharacterTextSplitterfrom langchain.embeddings import HuggingFaceEmbeddingsfrom langchain.vectorstores import FAISSfrom langchain.llms import CTransformersfrom langchain.memory import ConversationBufferMemoryfrom langchain.chains import ConversationalRetrievalChainimport sysDB_FAISS_PATH=‘vectorstore/db_faiss’loader=CSVLoader(file_path=‘data/2019.csv’,encoding=‘utf-8’,csv_args={‘delimiter’:‘,’})data=loader.load()#print(data)text_splitter=RecursiveCharacterTextSplitter(chunk_size=500,chunk_overlap=20)text_chunks=text_splitter.split_documents(data)print(len(text_chunks))print(text_chunks)embeddings = HuggingFaceEmbeddings(model_name=‘sentence-transformers/all-MiniLM-L6-v2’)docsearch=FAISS.from_documents(text_chunks,embeddings)docsearch.save_local(DB_FAISS_PATH)#query= ‘what is the value of GDP per capita of finland provided in the data’#docs=docsearch.similarity_search(query,k=3)#print(“Result”,docs)llm = CTransformers(model=“models/mistral-7b-v0.1.Q2_K.gguf”,model_type=“llama”,max_new_tokens=512,temperature=0.1)qa = ConversationalRetrievalChain.from_llm(llm, retriever=docsearch.as_retriever())while True:chat_history =#query= “What is the value of  GDP per capita of Finland provided in the data?”query = input(f"Input Prompt: ")if query == ‘exit’:print(‘Exiting’)sys.exit()if query == ‘’:continueresult = qa({“question”:query, “chat_history”:chat_history})print("Response: ", result[‘answer’])terminal Responseerror loading model: unknown (magic, version) combination: 46554747, 00000002; is this really a GGML file?llama_init_from_file: failed to load modelTraceback (most recent call last):File “d:\Clarista\dockerLLma\script.py”, line 31, inllm = CTransformers(model=“models/mistral-7b-v0.1.Q2_K.gguf”,^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^File “C:\Users\aksha\AppData\Local\Programs\Python\Python311\Lib\site-packages\langchain\load\serializable.py”, line 74, ininitsuper().init(**kwargs)File “pydantic\main.py”, line 339, in pydantic.main.BaseModel.initFile “pydantic\main.py”, line 1102, in pydantic.main.validate_modelFile “C:\Users\aksha\AppData\Local\Programs\Python\Python311\Lib\site-packages\langchain\llms\ctransformers.py”, line 70, in validate_environmentvalues[“client”] = AutoModelForCausalLM.from_pretrained(^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^File “C:\Users\aksha\AppData\Local\Programs\Python\Python311\Lib\site-packages\ctransformers\hub.py”, line 157, in from_pretrainedreturn LLM(^^^^File “C:\Users\aksha\AppData\Local\Programs\Python\Python311\Lib\site-packages\ctransformers\llm.py”, line 205, ininitraise RuntimeError(RuntimeError: Failed to create LLM ‘llama’ from ‘models/mistral-7b-v0.1.Q2_K.gguf’.
2023-11-07T06:20:38Z
model type should be mistral