ermiaazarkhalili/Carnice-9B-SFT-Fable5-GGUF overview
Carnice 9B SFT Fable5 GGUF GGUF quantizations of Carnice 9B SFT Fable5 https://huggingface.co/ermiaazarkhalili/Carnice 9B SFT Fable5 , for local inference with…
Runs locally from ~5.24 GB disk (8 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
Model Details
| Model ID | ermiaazarkhalili/Carnice-9B-SFT-Fable5-GGUF |
|---|---|
| Author | ermiaazarkhalili |
| Pipeline | text-generation |
| License | apache-2.0 |
| Base model | kai-os/Carnice-9b |
| Last modified | 2026-08-14T00:20:28.000Z |
Model README
---
license: apache-2.0
language:
- en
base_model: kai-os/Carnice-9b
datasets:
- ermiaazarkhalili/Fable-5-Complete-2M-Clean
library_name: transformers
pipeline_tag: text-generation
tags:
- gguf
- llama.cpp
- quantized
- ollama
- lm-studio
- text-generation
---
Carnice-9B-SFT-Fable5-GGUF
GGUF quantizations of Carnice-9B-SFT-Fable5, for local inference
with llama.cpp, Ollama, or LM Studio.
Overview
| Property | Value |
|---|---|
| Source model | Carnice-9B-SFT-Fable5 |
| Base model | kai-os/Carnice-9b |
| Training dataset | ermiaazarkhalili/Fable-5-Complete-2M-Clean |
| Architecture | Qwen3_5ForCausalLM |
| Parameters | 8.95 B |
| Layers | 32 |
| Vocab size | 248,320 |
| License | APACHE-2.0 |
| Developed by | Behrooz Azarkhalili |
Available quantizations
| File | Quant | Size | Notes |
|---|---|---:|---|
| carnice-9b-sft-fable5.q4_k_m.gguf | Q4_K_M | 5.24 GiB | Smallest here; the common choice for local inference on limited VRAM. |
| carnice-9b-sft-fable5.q5_k_m.gguf | Q5_K_M | 6.02 GiB | Balanced. The usual default when Q4_K_M feels lossy. |
| carnice-9b-sft-fable5.q8_0.gguf | Q8_0 | 8.87 GiB | Largest, closest to the merged weights. Use when disk is not the constraint. |
Sizes above are the actual file sizes in this repository, not estimates.
Quick start
Ollama
ollama pull hf.co/ermiaazarkhalili/Carnice-9B-SFT-Fable5-GGUF:Q4_K_M
llama.cpp
llama-cli -hf ermiaazarkhalili/Carnice-9B-SFT-Fable5-GGUF:Q4_K_M -p "Tell me a fable about a clever fox." -n 256
Download a single file
from huggingface_hub import hf_hub_download
path = hf_hub_download("ermiaazarkhalili/Carnice-9B-SFT-Fable5-GGUF", "carnice-9b-sft-fable5.q4_k_m.gguf")
print(path)
Limitations
- Quantization is lossy: outputs will not match the source model exactly, and the
effect grows as the quant level drops.
- Primarily English training data.
- Not safety-tuned. Use appropriate guardrails.
- Research and prototyping, not production without further evaluation.
Citation
@misc{azarkhalili2026_carnice_9b_sft_fable5_gguf,
author = {Azarkhalili, Behrooz},
title = {Carnice-9B-SFT-Fable5-GGUF},
year = {2026},
publisher = {Hugging Face},
url = {https://huggingface.co/ermiaazarkhalili/Carnice-9B-SFT-Fable5-GGUF}
}
Acknowledgments
- llama.cpp for the GGUF format and tooling
- Unsloth and Hugging Face TRL
- Compute Canada / DRAC for HPC resources
Run ermiaazarkhalili/Carnice-9B-SFT-Fable5-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models