LFM2.5-350M-ONNX

LFM2.5 is a new family of hybrid models designed for **on-device deployment**. It builds on the LFM2 architecture with extended pre-training and reinforcement learning. We recommend using it for data extraction, structured outputs, and tool use. It is not recommended for knowledge-intensive tasks and programming. 1. **Function definition**: We recommend providing the list of tools as a JSON object in the system prompt. You can also use the `tokenizer.apply_chat_template()` function with tools. 2. **Function call**: By default, LFM2.5 writes Pythonic function calls (a Python list between ` ` and ` ` special tokens), as the assistant answer. You can override this behavior by asking the model to output JSON function calls in the system prompt. 3. **Function execution**: The function call is executed, and the result is returned as a "tool" role. 4. **Final answer**: LFM2 interprets the outcome of the function call to address the original user prompt in plain text.

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