See `AutoTokenizer.from_pretrained` docstring.

Evaluate the model on the given data and update the data with the model responses. data: data input model: model to evaluate

This is the equivalent of torch.repeat_interleave(x, dim=1, repeats=n_rep). The hidden states go from (batch, num_key_value_heads, seqlen, he

Set the random seed for reproducibility. Parameters: seed (int): The seed to use for generating random numbers.

Disable the redundant torch default initialization to accelerate model creation.

Applies Rotary Position Embedding to the query and key tensors. Args: q (`torch.Tensor`): The query tensor. k (`torch.Tensor`): T

Given a list of sources, each is a conversation list. This transform: 1. Add signal '### ' at the beginning each sentence, with end signal '\

Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`]. Returns: `Dict[str,