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