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