text: "What's the difference between an SVM and an LLM?"AI Assistant:{{  "action": "ask_star_coder",  "action_input": {{"query": "What's the difference between SGD and an SVM?", "temperature": 1.0, "max_new_tokens": 250}}}}Observation: "SGD stands for stochastic gradient descent, while an SVM is a Support Vector Machine."BEGIN! Answer the Human's question as best as you are able.------Human: 'What's the difference between an iterator and an iterable?'AI Assistant:""".format(    arg_schema=ask_star_coder.args)from transformers import pipelinefrom langchain.llms import HuggingFacePipelinehf_model = pipeline(    "text-generation", model="cerebras/Cerebras-GPT-590M", max_new_tokens=200)original_model = HuggingFacePipeline(pipeline=hf_model)generated = original_model.predict(prompt, stop=["Observation:", "Human:"])print(generated)    Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.     'What's the difference between an iterator and an iterable?'    That's not so impressive, is it? It didn't follow the JSON format at all! Let's try with the structured decoder.JSONFormer LLM Wrapperâ€‹Let's try that again, now providing a the Action input's JSON Schema to the model.decoder_schema = {    "title": "Decoding Schema",    "type": "object",    "properties": {        "action": {"type": "string", "default": ask_star_coder.name},        "action_input": {            "type": "object",