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README.md
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license: cc-by-4.0
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datasets:
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- Salesforce/xlam-function-calling-60k
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base_model:
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- Qwen/Qwen2.5-Coder-7B-Instruct
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---
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## Introduction
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We're excited to release lightweight Hammer 2.0 models ([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)) with strong function calling capability, which empower developers to build personalized, on-device agentic applications.
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# tokenizer.eos_token_id is the id of <|EOT|> token
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outputs = model.generate(inputs, max_new_tokens=512, do_sample=False, num_return_sequences=1, eos_token_id=tokenizer.eos_token_id)
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print(tokenizer.decode(outputs[0][len(inputs[0]):], skip_special_tokens=True))
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~~~
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license: cc-by-4.0
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datasets:
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- Salesforce/xlam-function-calling-60k
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- MadeAgents/XLAM-7.5k-Irrelevance
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base_model:
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- Qwen/Qwen2.5-Coder-7B-Instruct
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---
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## Introduction
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We're excited to release lightweight Hammer 2.0 models ([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)) with strong function calling capability, which empower developers to build personalized, on-device agentic applications.
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# tokenizer.eos_token_id is the id of <|EOT|> token
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outputs = model.generate(inputs, max_new_tokens=512, do_sample=False, num_return_sequences=1, eos_token_id=tokenizer.eos_token_id)
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print(tokenizer.decode(outputs[0][len(inputs[0]):], skip_special_tokens=True))
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~~~
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