Triangle104/TAID-LLM-1.5B-Q5_K_M-GGUF

This model was converted to GGUF format from SakanaAI/TAID-LLM-1.5B using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

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TAID-LLM-1.5B is an English language model created through TAID (Temporally Adaptive Interpolated Distillation), our new knowledge distillation method. We used Qwen2-72B-Instruct as the teacher model and Qwen2-1.5B-Instruct as the student model.

    Model Details

Developed by: Sakana AI Model type: Autoregressive Language Model Language(s): English License: Apache License, Version 2.0 Paper: https://arxiv.org/abs/2501.16937 Blog: https://sakana.ai/taid/

    Uses

This model is provided for research and development purposes only and should be considered as an experimental prototype. It is not intended for commercial use or deployment in mission-critical environments. Use of this model is at the user's own risk, and its performance and outcomes are not guaranteed. Sakana AI shall not be liable for any direct, indirect, special, incidental, or consequential damages, or any loss arising from the use of this model, regardless of the results obtained. Users must fully understand the risks associated with the use of this model and use it at their own discretion.

    Acknowledgement

We would like to thank the developers of the source models for their contributions and for making their work available.

This model is based on results obtained from a project, JPNP20017, subsidized by the New Energy and Industrial Technology Development Organization (NEDO).

    Citation

@misc{sakana2025taid, title = {TAID: Temporally Adaptive Interpolated Distillation for Efficient Knowledge Transfer in Language Models}, author. = {Makoto Shing and Kou Misaki and Han Bao and Sho Yokoi and Takuya Akiba}, year = {2025}, eprint = {2501.16937}, archivePrefix = {arXiv}, primaryClass = {cs.LG}, url = {https://arxiv.org/abs/2501.16937}

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Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo Triangle104/TAID-LLM-1.5B-Q5_K_M-GGUF --hf-file taid-llm-1.5b-q5_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/TAID-LLM-1.5B-Q5_K_M-GGUF --hf-file taid-llm-1.5b-q5_k_m.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo Triangle104/TAID-LLM-1.5B-Q5_K_M-GGUF --hf-file taid-llm-1.5b-q5_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Triangle104/TAID-LLM-1.5B-Q5_K_M-GGUF --hf-file taid-llm-1.5b-q5_k_m.gguf -c 2048