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LLM Models Available for Fine-tuning

This table provides an overview of the Large Language Models (LLMs) available for fine-tuning, ordered approximately from most well-known to least familiar. It lists key details for each model, including its name, family, parameter count, context length, and additional features.

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Notes:

  • “vLLM Support” indicates whether the model is compatible with the vLLM (very Large Language Model) inference framework.
  • “LoRA Support” indicates if the vLLM support inference the model with multiple LorA Adapters. Read more
  • Context length is measured in tokens. (The model context can change by the target inference library)
  • Parameter count is shown in billions (B).
  • Links lead to the model’s page on Hugging Face or the official website when available.
This table provides a comprehensive overview of the available models, their sizes, capabilities, and support for various fine-tuning techniques. When choosing a model for fine-tuning, consider factors such as the model size, context length, and support for specific optimization techniques like vLLM and LoRA.