Make causal mask used for bi-directional self-attention.

Make causal mask used for bi-directional self-attention.

Calculate the mapping of global layer_idx to local layer_idx Returns: layer_map (Dict: int -> tuple(int, int, int)): mapping f

Calculate the mapping of global layer_idx to local layer_idx Returns: layer_map (Dict: int -> tuple(int, int, int)): mapping f

hdfs mkdir

For each param, if it is a tp-splited param, we all-gather from micro_dp group.

Process files, determine problem ID, and prepare configuration. Args: data: Dictionary containing file information

Prepares a quantized model for kbit training.

Prepares a model for PEFT training.

Run multiple scripts concurrently with limited parallelism. Args: scripts: List of scripts to execute language: Progr

Function wrapping the `_run_async` function.

Execute a single script in a MorphCloud Sandbox. Args: script: The script to execute language: Programming language

Run tests and evaluate results. Args: instance: The MorphCloud instance data: Dictionary containing runtime

Check if the input data is valid for training. Args: input_ids (list[`torch.LongTensor`]): List of tenso

Train on a batch of samples. Main training segment Args: inner_epoch (int): The current inner epoch epoch (i

Upload all necessary files to the instance. Args: instance: The MorphCloud instance local_files: Dictionary

r""" Add and load a reward modeling adapter. This method can only be used if the model is a `PeftModel` and if you have initialized th

Adds the optimizer hooks from a DeepSpeed ZeRO-3 model.

Fix common compilation errors for IOI problems.

Compute the BCO loss for a batch of policy and reference model log probabilities. Args: policy_chosen_logps: Log probabilities of

Build dataset for training. This builds the dataset from `load_dataset`, one should customize this function to train the model on its own dat

Build dataset for training. This builds the dataset from `load_dataset`, one should customize this function to train the model on its own dat

Build the memory references. The memory buffers are built using the build_memory_buffer API. This API will allocate a weight buffer pointer to the

Build ngram lookup for documents.

Calculate the loss for a batch of an unpacked sample Args: rewards (torch.Tensor): Differentiable reward

Estimate the average number of characters per token in the dataset.

Estimate the average number of characters per token in the dataset.

Check if the file contains a copyright notice, and add it if missing.

Check the consistency of the DataProto. Mainly for batch and non_tensor_batch We expose this function as a public one so that user can call th

Check server availability with retries on failure, within a total timeout duration. If the server is not up after the total timeout d

Only collect the data from the tp=0 and pp=last and every dp ranks

treat pp as dp. Only collect data on tp=0

Computing reward given input_ids. The transformers should output a tensor with shape [batch_size, sequence_length], and the value at [EOS]

Run the given model on the given batch of inputs, concatenating the chosen and rejected inputs together. We do this to avoid doing two forwar

Run the given model on the given batch of inputs, concatenating the chosen and rejected inputs together. We do this to avoid doing two forwar

Concatenate the chosen and rejected inputs into a single tensor. Args: batch: A batch of data. Must contain the keys 'chosen_inpu

Concatenate the `chosen` and `rejected` inputs from the batch into a single tensor for both the prompt and completion sequences.

Concatenate the chosen and rejected inputs into a single tensor. Args: batch: A batch of data. Must contain the keys 'chosen_inpu

r""" Simply iterates over the state dict and replaces the patterns in `mapping` with the corresponding values. Args: state_dict (`dic

Compute the CPO loss for a batch of policy and reference model log probabilities. Args: policy_chosen_logps: Log probabilities of

Creates and configures a FastAPI application instance. Args: args: An object containing configuration parameters for the application.

Creates and configures a FastAPI application instance for the MorphCloud router. Args: args: An object containing configuration

This function should return a class instance that delegates the calls to every cls in cls_dict

Args: model_name: actor_override_config_kwargs: Returns:

Creates a merge configuration for a DARE TIES merge of two models, with specified weights and densities.

Creates a merge configuration for a linear merge of two models with specified weights.

Creates a merge configuration for a SLERP merge of a model with a base model.

Creates a merge configuration for a TIES merge of two models, with specified weights and densities.

Creates a draft of a model card using the information available to the `Trainer`. Args: model_name (`str` or `None`, *op