model_parameters:
  model_name: "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B" # pretrained=model_name,trust_remote_code=boolean,revision=revision_to_use,model_parallel=True ... For a PEFT model, the pretrained model should be the one trained with PEFT and the base model below will contain the original model on which the adapters will be applied.
  tokenizer: null # name of tokenizer to use if different from the model's default
  subfolder: null # subfolder in the model's directory to use
  dtype: "float16"  # Specifying the model to be loaded in 4 bit uses BitsAndBytesConfig. The other option is to use "8bit" quantization.
  compile: true
  revision: "main" # revision to use
  trust_remote_code: true # Trust remote code
  model_parallel: null # Model parallel
  max_length: 2048 # maximum length of the input text and the generated text

  # should go in generation
  max_generation_toks: 256 # maximum number of tokens to generate
  batch_size: 10 # batch size to use
