ValueError: We cannot use hole to handle this generation the number of desired tokens exceeds the models max length

[pseudotensor]

  File "/home/ubuntu/h2ogpt/gradio_runner.py", line 1067, in bot
    for output_fun in fun1(*tuple(args_list)):
  File "/home/ubuntu/h2ogpt/generate.py", line 1056, in evaluate
    for r in run_qa_db(query=query,
  File "/home/ubuntu/h2ogpt/gpt_langchain.py", line 1250, in _run_qa_db
    raise thread.exc
  File "/home/ubuntu/h2ogpt/utils.py", line 314, in run
    self._return = self._target(*self._args, **self._kwargs)
  File "/home/ubuntu/miniconda3/envs/h2ollm/lib/python3.10/site-packages/langchain/chains/base.py", line 140, in __call__
    raise e
  File "/home/ubuntu/miniconda3/envs/h2ollm/lib/python3.10/site-packages/langchain/chains/base.py", line 134, in __call__
    self._call(inputs, run_manager=run_manager)
  File "/home/ubuntu/miniconda3/envs/h2ollm/lib/python3.10/site-packages/langchain/chains/combine_documents/base.py", line 84, in _call
    output, extra_return_dict = self.combine_docs(
  File "/home/ubuntu/miniconda3/envs/h2ollm/lib/python3.10/site-packages/langchain/chains/combine_documents/stuff.py", line 87, in combine_docs
    return self.llm_chain.predict(callbacks=callbacks, **inputs), {}
  File "/home/ubuntu/miniconda3/envs/h2ollm/lib/python3.10/site-packages/langchain/chains/llm.py", line 213, in predict
    return self(kwargs, callbacks=callbacks)[self.output_key]
  File "/home/ubuntu/miniconda3/envs/h2ollm/lib/python3.10/site-packages/langchain/chains/base.py", line 140, in __call__
    raise e
  File "/home/ubuntu/miniconda3/envs/h2ollm/lib/python3.10/site-packages/langchain/chains/base.py", line 134, in __call__
    self._call(inputs, run_manager=run_manager)
  File "/home/ubuntu/miniconda3/envs/h2ollm/lib/python3.10/site-packages/langchain/chains/llm.py", line 69, in _call
    response = self.generate([inputs], run_manager=run_manager)
  File "/home/ubuntu/miniconda3/envs/h2ollm/lib/python3.10/site-packages/langchain/chains/llm.py", line 79, in generate
    return self.llm.generate_prompt(
  File "/home/ubuntu/miniconda3/envs/h2ollm/lib/python3.10/site-packages/langchain/llms/base.py", line 134, in generate_prompt
    return self.generate(prompt_strings, stop=stop, callbacks=callbacks)
  File "/home/ubuntu/miniconda3/envs/h2ollm/lib/python3.10/site-packages/langchain/llms/base.py", line 191, in generate
    raise e
  File "/home/ubuntu/miniconda3/envs/h2ollm/lib/python3.10/site-packages/langchain/llms/base.py", line 185, in generate
    self._generate(prompts, stop=stop, run_manager=run_manager)
  File "/home/ubuntu/miniconda3/envs/h2ollm/lib/python3.10/site-packages/langchain/llms/base.py", line 436, in _generate
    self._call(prompt, stop=stop, run_manager=run_manager)
  File "/home/ubuntu/miniconda3/envs/h2ollm/lib/python3.10/site-packages/langchain/llms/huggingface_pipeline.py", line 168, in _call
    response = self.pipeline(prompt)
  File "/home/ubuntu/miniconda3/envs/h2ollm/lib/python3.10/site-packages/transformers/pipelines/text_generation.py", line 209, in __call__
    return super().__call__(text_inputs, **kwargs)
  File "/home/ubuntu/miniconda3/envs/h2ollm/lib/python3.10/site-packages/transformers/pipelines/base.py", line 1109, in __call__
    return self.run_single(inputs, preprocess_params, forward_params, postprocess_params)
  File "/home/ubuntu/miniconda3/envs/h2ollm/lib/python3.10/site-packages/transformers/pipelines/base.py", line 1115, in run_single
    model_inputs = self.preprocess(inputs, **preprocess_params)
  File "/home/ubuntu/h2ogpt/h2oai_pipeline.py", line 79, in preprocess
    return super().preprocess(prompt_text, prefix=prefix, handle_long_generation=handle_long_generation,
  File "/home/ubuntu/miniconda3/envs/h2ollm/lib/python3.10/site-packages/transformers/pipelines/text_generation.py", line 228, in preprocess
    raise ValueError(
ValueError: We cannot use `hole` to handle this generation the number of desired tokens exceeds the models max length