SSD-SSM forward pass. Args: x: Input of shape (batch_size, seq_len, num_heads, head_dim). dt: Time deltas of shape (seq_len, num_

Ensures the model is available locally. If the path does not exist locally, it is downloaded from the Hugging Face Hub. Args: pa

Rearrange the cache into temporal order, slicing off the end if unused.

Apply XTC sampling to the logits. Args: logits: The logits from the model's output. xtc_probability (float): Probability of

Generate responses for the given batch of prompts. Args: model (nn.Module): The language model. tokenizer (PreTrainedTokenizer

Filter the batch to keep only the specified indices.

Apply min-p sampling to the logprobs. Min-p keeps all tokens that are above a minimum probability, scaled by the probability of the most

Sample from only the top K tokens ranked by probability. Args: logprobs: A vector of log probabilities. top_k (int): Top k t

Build a learning rate schedule from the given config.