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Update app.py
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app.py
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@@ -48,6 +48,11 @@ from langchain import PromptTemplate
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from langchain import LLMChain
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from langchain.llms import CTransformers
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# Update the model path to use the Hugging Face model identifier
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llm = CTransformers(model='TheBloke/Llama-2-7B-Chat-GGML',
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model_file='llama-2-7b-chat.ggmlv3.q3_K_S.bin',
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@@ -56,6 +61,12 @@ llm = CTransformers(model='TheBloke/Llama-2-7B-Chat-GGML',
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'temperature': 0.01}
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)
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def greet(my_prompt):
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B_INST, E_INST = "[INST]", "[/INST]"
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@@ -90,7 +101,7 @@ def greet(my_prompt):
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prompt = PromptTemplate(template=template, input_variables=["text"])
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LLM_Chain = LLMChain(prompt=prompt, llm=llm)
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# print(LLM_Chain.run("How are you"))
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from langchain import LLMChain
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from langchain.llms import CTransformers
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from langchain.memory import ConversationBufferWindowMemory
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memory = ConversationBufferWindowMemory()
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# Update the model path to use the Hugging Face model identifier
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llm = CTransformers(model='TheBloke/Llama-2-7B-Chat-GGML',
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model_file='llama-2-7b-chat.ggmlv3.q3_K_S.bin',
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'temperature': 0.01}
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)
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# convo = ConversationChain(
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# llm=llm,
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# memory=memory
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# )
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# convo.run("Who won the first cricket world cup?")
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def greet(my_prompt):
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B_INST, E_INST = "[INST]", "[/INST]"
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prompt = PromptTemplate(template=template, input_variables=["text"])
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LLM_Chain = LLMChain(prompt=prompt, llm=llm, memory=memory)
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# print(LLM_Chain.run("How are you"))
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