ethicalabs/Kurtis-E1-SmolLM2-1.7B-Instruct-Q4_K_M-GGUF overview
ethicalabs/Kurtis E1 SmolLM2 1.7B Instruct Q4 K M GGUF WARNING This repository contains experimental models designed strictly for academic evaluation and resea…
Runs locally from ~1006.7 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| kurtis-e1-smollm2-1.7b-instruct-q4_k_m.gguf | GGUF | Q4_K_M | 1006.7 MB | Download |
Model Details
| Model ID | ethicalabs/Kurtis-E1-SmolLM2-1.7B-Instruct-Q4_K_M-GGUF |
|---|---|
| Author | ethicalabs |
| Pipeline | text-generation |
| License | mit |
| Base model | ethicalabs/Kurtis-E1-SmolLM2-1.7B-Instruct |
| Last modified | 2026-06-19T14:57:35.000Z |
Model README
---
base_model: ethicalabs/Kurtis-E1-SmolLM2-1.7B-Instruct
datasets:
- ethicalabs/Kurtis-E1-SFT
language:
- en
library_name: transformers
license: mit
pipeline_tag: text-generation
tags:
- text-generation-inference
- llama-cpp
- gguf-my-repo
---
ethicalabs/Kurtis-E1-SmolLM2-1.7B-Instruct-Q4_K_M-GGUF
> [!WARNING]
> This repository contains experimental models designed strictly for academic evaluation and research purposes.
>
> Critical Constraints:
> * No Production Deployment: Experimental models must not be deployed in commercial, enterprise, or mission-critical environments under any circumstances.
> * No Liability: Experimental models are provided "as-is" without warranties of any kind. The developers assume zero liability for downstream consequences, system integration failures, or regulatory non-compliance resulting from unauthorized deployment.
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 ethicalabs/Kurtis-E1-SmolLM2-1.7B-Instruct-Q4_K_M-GGUF --hf-file kurtis-e1-smollm2-1.7b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo ethicalabs/Kurtis-E1-SmolLM2-1.7B-Instruct-Q4_K_M-GGUF --hf-file kurtis-e1-smollm2-1.7b-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 ethicalabs/Kurtis-E1-SmolLM2-1.7B-Instruct-Q4_K_M-GGUF --hf-file kurtis-e1-smollm2-1.7b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo ethicalabs/Kurtis-E1-SmolLM2-1.7B-Instruct-Q4_K_M-GGUF --hf-file kurtis-e1-smollm2-1.7b-instruct-q4_k_m.gguf -c 2048Run ethicalabs/Kurtis-E1-SmolLM2-1.7B-Instruct-Q4_K_M-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models