diff --git a/README.md b/README.md index d0f7552..36fc6a5 100644 --- a/README.md +++ b/README.md @@ -43,10 +43,10 @@ question = tg.Variable(question_string, role_description="question to the LLM", answer = model(question) ``` - answer: To determine how long it will take to dry 30 shirts under the sun, - we can use a proportional relationship based on the given information. - Here’s the step-by-step reasoning: [.....] - So, it will take 1.2 hours (or 1 hour and 12 minutes) to dry 30 shirts under the sun. +> answer: To determine how long it will take to dry 30 shirts under the sun, +> we can use a proportional relationship based on the given information. +> Here’s the step-by-step reasoning: [.....] +> So, it will take 1.2 hours (or 1 hour and 12 minutes) to dry 30 shirts under the sun. As you can see, **the model's answer is incorrect.** We can optimize the answer using TextGrad to get the correct answer. @@ -63,9 +63,9 @@ evaluation_instruction = f"Here's a question: {question_string}. Evaluate any gi # TextLoss is a natural-language specified loss function that describes how we want to evaluate the reasoning. loss_fn = tg.TextLoss(evaluation_instruction) ``` - loss: [...] Your step-by-step reasoning is clear and logical, - but it contains a critical flaw in the assumption that drying time is directly proportional - to the number of shirts. [...] +> loss: [...] Your step-by-step reasoning is clear and logical, +> but it contains a critical flaw in the assumption that drying time is directly proportional +> to the number of shirts. [...] ```python # Step 3: Do the loss computation, backward pass, and update the punchline. Exact same syntax as PyTorch! @@ -75,8 +75,8 @@ optimizer.step() answer ``` - answer: It will still take 1 hour to dry 30 shirts under the sun, - assuming they are all laid out properly to receive equal sunlight. +> answer: It will still take 1 hour to dry 30 shirts under the sun, +> assuming they are all laid out properly to receive equal sunlight.