Updated docstring for run.py

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Carlos D. Escobar-Valbuena 2024-03-18 16:17:43 -05:00 committed by GitHub
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run.py
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@ -22,6 +22,27 @@ CKPT_PATH = "./checkpoints/"
def main():
"""
Initializes and runs a text generation model using predefined model configurations and inference settings.
This function sets up a language model with specific configurations, including model architecture details
(e.g., embedding sizes, number of layers, attention heads, and MoE settings) and text generation settings
(e.g., vocabulary size, token identifiers). It initializes an inference runner with the model, checkpoint
path, tokenizer, and mesh configuration. The inference runner is then used to generate text based on a
given prompt and output the result.
The process involves:
- Creating a `LanguageModelConfig` instance with specified model parameters, including transformer
configurations and quantization settings for weights.
- Initializing an `InferenceRunner` with the model configuration, batch size per device, checkpoint path,
and other relevant settings.
- Calling the `initialize` method on the inference runner to prepare the model and tokenizer for inference.
- Generating text based on a provided prompt using the `sample_from_model` function, which internally
manages the sampling process through the inference runner.
Output:
- Prints the generated text continuation for a prompt to the standard output.
"""
grok_1_model = LanguageModelConfig(
vocab_size=128 * 1024,
pad_token=0,