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README.md

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+---
+license: apache-2.0
+base_model: allura-org/Q3-8B-Kintsugi
+library_name: transformers
+tags:
+- mergekit
+- axolotl
+- unsloth
+- roleplay
+- conversational
+- llama-cpp
+- gguf-my-repo
+datasets:
+- PygmalionAI/PIPPA
+- Alfitaria/nemotron-ultra-reasoning-synthkink
+- PocketDoc/Dans-Prosemaxx-Gutenberg
+- FreedomIntelligence/Medical-R1-Distill-Data
+- cognitivecomputations/SystemChat-2.0
+- allenai/tulu-3-sft-personas-instruction-following
+- kalomaze/Opus_Instruct_25k
+- simplescaling/s1K-claude-3-7-sonnet
+- ai2-adapt-dev/flan_v2_converted
+- grimulkan/theory-of-mind
+- grimulkan/physical-reasoning
+- nvidia/HelpSteer3
+- nbeerbower/gutenberg2-dpo
+- nbeerbower/gutenberg-moderne-dpo
+- nbeerbower/Purpura-DPO
+- antiven0m/physical-reasoning-dpo
+- allenai/tulu-3-IF-augmented-on-policy-70b
+- NobodyExistsOnTheInternet/system-message-DPO
+---
+
+# Triangle104/Q3-8B-Kintsugi-Q4_K_M-GGUF
+This model was converted to GGUF format from [`allura-org/Q3-8B-Kintsugi`](https://huggingface.co/allura-org/Q3-8B-Kintsugi) 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/allura-org/Q3-8B-Kintsugi) 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-cli --hf-repo Triangle104/Q3-8B-Kintsugi-Q4_K_M-GGUF --hf-file q3-8b-kintsugi-q4_k_m.gguf -p "The meaning to life and the universe is"
+```
+
+### Server:
+```bash
+llama-server --hf-repo Triangle104/Q3-8B-Kintsugi-Q4_K_M-GGUF --hf-file q3-8b-kintsugi-q4_k_m.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.
+```
+./llama-cli --hf-repo Triangle104/Q3-8B-Kintsugi-Q4_K_M-GGUF --hf-file q3-8b-kintsugi-q4_k_m.gguf -p "The meaning to life and the universe is"
+```
+or 
+```
+./llama-server --hf-repo Triangle104/Q3-8B-Kintsugi-Q4_K_M-GGUF --hf-file q3-8b-kintsugi-q4_k_m.gguf -c 2048
+```