Update examples
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2 changed files with 26 additions and 4 deletions
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@ -4,11 +4,11 @@ import argparse
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from llama_cpp import Llama
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parser = argparse.ArgumentParser()
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parser.add_argument("-m", "--model", type=str, default="../models/...")
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parser.add_argument("-m", "--model", type=str, default=".//models/...")
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args = parser.parse_args()
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llm = Llama(model_path=args.model)
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output = llm("Question: What are the names of the planets in the solar system? Answer: ", max_tokens=48, stop=["Q:", "\n"], echo=False)
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output = llm("Question: What are the names of the planets in the solar system? Answer: ", max_tokens=48, stop=["Q:", "\n"], echo=True)
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print(json.dumps(output, indent=2))
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@ -1,3 +1,5 @@
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import argparse
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from llama_cpp import Llama
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from langchain.llms.base import LLM
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@ -24,6 +26,26 @@ class LlamaLLM(LLM):
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def _identifying_params(self) -> Mapping[str, Any]:
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return {"model_path": self.model_path}
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llm = LlamaLLM(model_path="models/...")
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parser = argparse.ArgumentParser()
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parser.add_argument("-m", "--model", type=str, default="./models/...")
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args = parser.parse_args()
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print(llm("Question: What is the capital of France? Answer: ", stop=["Question:", "\n"]))
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# Load the model
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llm = LlamaLLM(model_path=args.model)
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# Basic Q&A
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answer = llm("Question: What is the capital of France? Answer: ", stop=["Question:", "\n"])
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print(f"Answer: {answer.strip()}")
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# Using in a chain
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from langchain.prompts import PromptTemplate
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from langchain.chains import LLMChain
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prompt = PromptTemplate(
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input_variables=["product"],
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template="\n\n### Instruction:\nWrite a good name for a company that makes {product}\n\n### Response:\n",
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)
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chain = LLMChain(llm=llm, prompt=prompt)
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# Run the chain only specifying the input variable.
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print(chain.run("colorful socks"))
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