--- license: apache-2.0 language: - en library_name: gguf pipeline_tag: text-generation tags: - gguf - llama.cpp - quantized - granite - reasoning - unsloth - text-generation base_model: ermiaazarkhalili/Granite-4.1-8B-SFT-Claude-Opus-Reasoning-Unsloth datasets: - ermiaazarkhalili/claude-reasoning-distillation --- # Granite-4.1-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF GGUF quantizations of [Granite-4.1-8B-SFT-Claude-Opus-Reasoning-Unsloth](https://huggingface.co/ermiaazarkhalili/Granite-4.1-8B-SFT-Claude-Opus-Reasoning-Unsloth) for **CPU and edge inference** with [llama.cpp](https://github.com/ggerganov/llama.cpp), [Ollama](https://ollama.com), LM Studio, and other GGUF runtimes. This model is a fine-tune of [Granite 4.1-8B](https://huggingface.co/ibm-granite/granite-4.1-8b) for **reasoning distillation (chain-of-thought)**, trained with [Unsloth](https://github.com/unslothai/unsloth) on [claude-reasoning-distillation](https://huggingface.co/datasets/ermiaazarkhalili/claude-reasoning-distillation). - **Full-precision model:** [Granite-4.1-8B-SFT-Claude-Opus-Reasoning-Unsloth](https://huggingface.co/ermiaazarkhalili/Granite-4.1-8B-SFT-Claude-Opus-Reasoning-Unsloth) - **Base model:** [Granite 4.1-8B](https://huggingface.co/ibm-granite/granite-4.1-8b) - **Parameters:** 8B ## Available Quantizations | Quant | Size | Recommended Use | File | |-------|------|-----------------|------| | `Q2_K` | 3.41 GB | Smallest, lowest quality — quick tests / very constrained devices | [`granite-4.1-8b-sft-claude-opus-reasoning-unsloth.q2_k.gguf`](https://huggingface.co/ermiaazarkhalili/Granite-4.1-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF/blob/main/granite-4.1-8b-sft-claude-opus-reasoning-unsloth.q2_k.gguf) | | `Q3_K_M` | 4.35 GB | Small, acceptable quality | [`granite-4.1-8b-sft-claude-opus-reasoning-unsloth.q3_k_m.gguf`](https://huggingface.co/ermiaazarkhalili/Granite-4.1-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF/blob/main/granite-4.1-8b-sft-claude-opus-reasoning-unsloth.q3_k_m.gguf) | | `Q4_K_M` | 5.35 GB | Recommended — best size/quality balance | [`granite-4.1-8b-sft-claude-opus-reasoning-unsloth.q4_k_m.gguf`](https://huggingface.co/ermiaazarkhalili/Granite-4.1-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF/blob/main/granite-4.1-8b-sft-claude-opus-reasoning-unsloth.q4_k_m.gguf) | | `Q5_K_M` | 6.25 GB | High quality, larger | [`granite-4.1-8b-sft-claude-opus-reasoning-unsloth.q5_k_m.gguf`](https://huggingface.co/ermiaazarkhalili/Granite-4.1-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF/blob/main/granite-4.1-8b-sft-claude-opus-reasoning-unsloth.q5_k_m.gguf) | | `Q6_K` | 7.22 GB | Very high quality, near-fp16 | [`granite-4.1-8b-sft-claude-opus-reasoning-unsloth.q6_k.gguf`](https://huggingface.co/ermiaazarkhalili/Granite-4.1-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF/blob/main/granite-4.1-8b-sft-claude-opus-reasoning-unsloth.q6_k.gguf) | | `Q8_0` | 9.35 GB | Near-lossless, largest | [`granite-4.1-8b-sft-claude-opus-reasoning-unsloth.q8_0.gguf`](https://huggingface.co/ermiaazarkhalili/Granite-4.1-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF/blob/main/granite-4.1-8b-sft-claude-opus-reasoning-unsloth.q8_0.gguf) | `Q4_K_M` is the recommended default for most users. ## Usage ### Download a single quant ```bash pip install -U "huggingface_hub[cli]" hf download ermiaazarkhalili/Granite-4.1-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF \ --include "*q4_k_m*.gguf" --local-dir ./Granite-4.1-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF ``` ### llama.cpp ```bash # build: https://github.com/ggerganov/llama.cpp ./llama-cli -m ./Granite-4.1-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF/granite-4.1-8b-sft-claude-opus-reasoning-unsloth.q2_k.gguf \ -p "Solve step by step: What is the sum of the first 10 prime numbers?" -n 512 ``` ### Ollama ```bash ollama run hf.co/ermiaazarkhalili/Granite-4.1-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF:Q4_K_M "Solve step by step: What is the sum of the first 10 prime numbers?" ``` ## Training Outcome | Metric | Value | |--------|-------| | SLURM Job ID | `38330897` | | Runtime | 32m 49s | | Final Training Loss | 0.7895 | | Peak VRAM | 9.26 GB | | GPU | H100 80GB HBM3 (MIG 3g.40gb) | ## License APACHE-2.0 — see the [base model](https://huggingface.co/ibm-granite/granite-4.1-8b) for full terms. ## Acknowledgments - [Unsloth](https://github.com/unslothai/unsloth) for 2x faster fine-tuning - [llama.cpp](https://github.com/ggerganov/llama.cpp) for GGUF quantization - Base model developers (ibm-granite) - [Compute Canada / DRAC](https://alliancecan.ca/) for HPC resources