This function adds a wrapper after the output of a function call in the method named `method_name`. Only calls directly in the method are aff

This function adds a wrapper after the output of a function call in the method named `method_name`. Only calls directly in the method are af

Create INT4 dense GEMM instance (compatible with old interface)

Setup the optimizer and the learning rate scheduler. We provide a reasonable default that works well. If you want to use something e

Create sparse GEMM instance (compatible with old interface)

Distribute the model across available GPUs. NB: only implemented for Llama-2.

Distribute the model across available GPUs. NB: only implemented for Llama-2.

Distribute the model across available GPUs. NB: only implemented for Llama-2/3/Qwen-2.

Args: hidden_states (`torch.FloatTensor`): input to the layer of shape `(batch, seq_len, embed_dim)` attention_mask (

r""" Args: labels (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*): Labels for computing

r""" labels (`torch.LongTensor` of shape `(batch_size,)`, *optional*): Labels for computing the sequence classification/regression

r""" start_positions (`torch.LongTensor` of shape `(batch_size,)`, *optional*): Labels for position (index) of the start of the la

Args: hidden_states (`torch.FloatTensor`): input to the layer of shape `(batch, seq_len, embed_dim)` attention_mask (

r""" Args: labels (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*): Labels for computing

r""" labels (`torch.LongTensor` of shape `(batch_size,)`, *optional*): Labels for computing the sequence classification/regression

r""" start_positions (`torch.LongTensor` of shape `(batch_size,)`, *optional*): Labels for position (index) of the start of the la