Update README.md

README.md

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 ## Introduction
 The Hammer2.0 series models have been released, including versions such as [0.5b](https://huggingface.co/MadeAgents/Hammer2.0-0.5b), [1.5b](https://huggingface.co/MadeAgents/Hammer2.0-1.5b), [3b](https://huggingface.co/MadeAgents/Hammer2.0-3b), and [7b](https://huggingface.co/MadeAgents/Hammer2.0-7b). Compared to the Hammer 1.0 series, the Hammer 2.0 series has stronger performance in function calling.
-Take Hammer2.0-1.5b as an example, it is a fine-tuned model based on [Qwen2.5-Coder-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B-Instruct). By training with the APIGen Function Calling Datasets containing 60,000 samples and combining innovative training techniques such as function masking, function shuffling, and prompt optimization, Hammer2.0-1.5b has achieved excellent performance in numerous benchmark tests.
+Take Hammer2.0-7b as an example, it is a fine-tuned model based on [Qwen2.5-Coder-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct). By training with the APIGen Function Calling Datasets containing 60,000 samples and combining innovative training techniques such as function masking, function shuffling, and prompt optimization, Hammer2.0-7b has achieved excellent performance in numerous benchmark tests.
 Whether in the Berkeley Function - Calling Leaderboard or other academic benchmark tests, the Hammer2.0 series models have demonstrated stronger generalization ability and can better meet the needs of users in function calling.
 In short, the Hammer2.0 series models provide users with a more powerful and efficient language model solution.