| base_model: Team-ACE/ToolACE-8B | |
| datasets: | |
| - Team-ACE/ToolACE | |
| language: | |
| - en | |
| license: apache-2.0 | |
| metrics: | |
| - accuracy | |
| tags: | |
| - code | |
| - llama-cpp | |
| - gguf-my-repo | |
| # Nekuromento/ToolACE-8B-Q5_K_M-GGUF | |
| This model was converted to GGUF format from [`Team-ACE/ToolACE-8B`](https://huggingface.co/Team-ACE/ToolACE-8B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. | |
| Refer to the [original model card](https://huggingface.co/Team-ACE/ToolACE-8B) for more details on the model. | |
| ## Use with llama.cpp | |
| Install llama.cpp through brew (works on Mac and Linux) | |
| ```bash | |
| brew install llama.cpp | |
| ``` | |
| Invoke the llama.cpp server or the CLI. | |
| ### CLI: | |
| ```bash | |
| llama-cli --hf-repo Nekuromento/ToolACE-8B-Q5_K_M-GGUF --hf-file toolace-8b-q5_k_m.gguf -p "The meaning to life and the universe is" | |
| ``` | |
| ### Server: | |
| ```bash | |
| llama-server --hf-repo Nekuromento/ToolACE-8B-Q5_K_M-GGUF --hf-file toolace-8b-q5_k_m.gguf -c 2048 | |
| ``` | |
| Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) 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 Nekuromento/ToolACE-8B-Q5_K_M-GGUF --hf-file toolace-8b-q5_k_m.gguf -p "The meaning to life and the universe is" | |
| ``` | |
| or | |
| ``` | |
| ./llama-server --hf-repo Nekuromento/ToolACE-8B-Q5_K_M-GGUF --hf-file toolace-8b-q5_k_m.gguf -c 2048 | |
| ``` | |