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  - Salesforce/xlam-function-calling-60k
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  base_model: Qwen/Qwen2-1.5B-Instruct
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  ---
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- # Hammer 2.0 Series
 
 
 
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  We're excited to introduce Hammer 2.0, the latest in our Hammer Large Language Models series designed to enhance AI function calling. Differing from existing models focusing on training data refinement, Hammer optimizes performance primarily through advanced training techniques. In this version, we release a number of models with sizes ranging from 0.5B to 7B:
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  [0.5B](https://huggingface.co/MadeAgents/Hammer2.0-0.5b),
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  [1.5B](https://huggingface.co/MadeAgents/Hammer2.0-1.5b),
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  [4B](https://huggingface.co/MadeAgents/Hammer2.0-3b), and [7B](https://huggingface.co/MadeAgents/Hammer2.0-0.5b).
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- # Hammer-1.5b Function Calling Model
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  ## Introduction
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  **Hammer** is a series of cutting-edge Large Language Models (LLMs) crafted to boost the critical capability of AI agents: function calling. Differing from existing models focusing on training data refinement, Hammer optimizes performance primarily through advanced training techniques. Focusing on on-device applications, we release a number of models from 1.5B, 4B to 7B parameters.
 
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  - Salesforce/xlam-function-calling-60k
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  base_model: Qwen/Qwen2-1.5B-Instruct
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  ---
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+ # Hammer-1.5b Function Calling Model
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+
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+ ## Hammer 2.0 Series Introduction
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  We're excited to introduce Hammer 2.0, the latest in our Hammer Large Language Models series designed to enhance AI function calling. Differing from existing models focusing on training data refinement, Hammer optimizes performance primarily through advanced training techniques. In this version, we release a number of models with sizes ranging from 0.5B to 7B:
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  [0.5B](https://huggingface.co/MadeAgents/Hammer2.0-0.5b),
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  [1.5B](https://huggingface.co/MadeAgents/Hammer2.0-1.5b),
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  [4B](https://huggingface.co/MadeAgents/Hammer2.0-3b), and [7B](https://huggingface.co/MadeAgents/Hammer2.0-0.5b).
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  ## Introduction
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  **Hammer** is a series of cutting-edge Large Language Models (LLMs) crafted to boost the critical capability of AI agents: function calling. Differing from existing models focusing on training data refinement, Hammer optimizes performance primarily through advanced training techniques. Focusing on on-device applications, we release a number of models from 1.5B, 4B to 7B parameters.