samhavens
commented
1 year ago That is a very high temperature, you might want to bring it down to closer to 0.1 or so. repetition penalty is also very high
You can see the defaults in the demo here https://huggingface.co/spaces/mosaicml/mpt-7b-instruct/blob/main/app.py#L157
thusithaC
Hi,
What is the appropriate format for providing an input context to the prompt? I tried below but, seems the model fails at seemingly easy questions similar models can answer, and I'm giving it the benefit of the doubt that it is a prompt issue or something with my config? .
model_name = 'mosaicml/mpt-7b-instruct'
INSTRUCTION_KEY = "### Instruction:" RESPONSE_KEY = "### Response:" END_KEY = "### End" INTRO_BLURB = "Below is an instruction that describes a task. Write a response that appropriately completes the request based on the Input if any input is provided." INPUT_CONTEXT = """### Input: {context}""" PROMPT_FOR_GENERATION_FORMAT = """{intro} {input_context} {instruction_key} {instruction} {response_key} """.format( intro=INTRO_BLURB, input_context=INPUT_CONTEXT, instruction_key=INSTRUCTION_KEY, instruction="{instruction}", response_key=RESPONSE_KEY, )config and result:
`def get_input_data(inputs, context=""): data = { "inputs": inputs, "context": context, "temperature": 1, "top_p": 0.92, "top_k": 0, "max_length": 1024, "use_cache": True, "do_sample": False, "repetition_penalty" : 1.1 } return data
prompt = "what is Driver protection cover?" context = "Driver Protection Cover is extra cover We automatically provide with Your NRMA Compulsory Third Party (CTP) Insurance on most passenger Vehicles and some goods Vehicles. See Table 1. for the Vehicles that We cover and those We do not cover.Driver Protection Cover provides the driver of a covered Vehicle who suffers one or more of the injuries listed in the specified injuries table with a set payment if the driver was at-fault in the accident in which they were injured"
response = predict_fn(get_input_data(inputs=prompt, context=context), model_and_tokenizer) response`
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