asynclee/SmolLM2-360M-Instruct-Q4_K_M-GGUF
By asynclee · ↓ 11 · ♥ 0 · Updated 2025-01-15
What's in this repo
This page lists the files in asynclee/SmolLM2-360M-Instruct-Q4_K_M-GGUF.
- No .onnx files in this repository
- 3 files, including 1 .md, 1 .gguf
- Last updated 2025-01-15
ONNX files
This repository has no .onnx files. See the full file list on the right for other formats.
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
asynclee/SmolLM2-360M-Instruct-Q4_K_M-GGUF
This model was converted to GGUF format from HuggingFaceTB/SmolLM2-360M-Instruct using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
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 asynclee/SmolLM2-360M-Instruct-Q4_K_M-GGUF --hf-file smollm2-360m-instruct-q4_k_m.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo asynclee/SmolLM2-360M-Instruct-Q4_K_M-GGUF --hf-file smollm2-360m-instruct-q4_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 asynclee/SmolLM2-360M-Instruct-Q4_K_M-GGUF --hf-file smollm2-360m-instruct-q4_k_m.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo asynclee/SmolLM2-360M-Instruct-Q4_K_M-GGUF --hf-file smollm2-360m-instruct-q4_k_m.gguf -c 2048
Model info
Created: 2025-01-15
Updated: 2025-01-15
View on Hugging FaceFiles (3)
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