license: apache-2.0 | |
tags: | |
- llama-cpp | |
- gguf-my-repo | |
base_model: Bin12345/AutoCoder | |
# aevalone/AutoCoder-Q6_K-GGUF | |
This model was converted to GGUF format from [`Bin12345/AutoCoder`](https://huggingface.co/Bin12345/AutoCoder) 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/Bin12345/AutoCoder) 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 --hf-repo aevalone/AutoCoder-Q6_K-GGUF --hf-file autocoder-q6_k.gguf -p "The meaning to life and the universe is" | |
``` | |
### Server: | |
```bash | |
llama-server --hf-repo aevalone/AutoCoder-Q6_K-GGUF --hf-file autocoder-q6_k.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. | |
``` | |
./main --hf-repo aevalone/AutoCoder-Q6_K-GGUF --hf-file autocoder-q6_k.gguf -p "The meaning to life and the universe is" | |
``` | |
or | |
``` | |
./server --hf-repo aevalone/AutoCoder-Q6_K-GGUF --hf-file autocoder-q6_k.gguf -c 2048 | |
``` | |