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--- |
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language: en |
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tags: |
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- llama |
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- llama-3.2 |
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- function-calling |
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- instruction-tuning |
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- conversational |
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license: llama2 |
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--- |
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# NeuralTau Functions v1 |
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This is a full version of the model fine-tuned on the full dataset. |
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The model is trained to understand and follow complex instructions, providing detailed explanations and performing function-like operations in a conversational manner. |
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## Model Variants Available |
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- 16-bit full model |
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- GGUF Q4_K_M quantized version (recommended for most use cases) |
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- GGUF Q8_0 quantized version (higher quality, larger size) |
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## Training Details |
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- Base Model: unsloth/Llama-3.2-3B-Instruct |
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- Training Dataset: 0xroyce/NeuralTau-With-Functions-chat (https://huggingface.co/datasets/0xroyce/NeuralTau-With-Functions-chat) |
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- Training Method: LoRA fine-tuning with r=16 |
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- Library Used: Unsloth |
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- Parameters: 3 billion |
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## Usage |
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The model follows the Llama chat format. You can interact with it using: |
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```python |
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messages = [ |
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{"role": "user", "content": "Your instruction or question here"}, |
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] |
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``` |
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Function calling example: |
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``` |
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>>> how do i do a function for weather? use <tool_call> </tool_call> |
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<tool_call> |
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{"arguments": {"location": "Los Angeles", "time_period": "current"}, "name": "get_weather_data"} |
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</tool_call> |
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``` |
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## Model Capabilities |
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- Understanding and following complex instructions |
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- Providing detailed explanations and analysis |
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- Breaking down complex topics into understandable components |
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- Function-like operations and systematic problem-solving |
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- Maintaining context in multi-turn conversations |
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- Generating clear and structured responses |
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## License |
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This model is subject to the Llama 2 license. |
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