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--- |
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base_model: ibm-granite/granite-3.3-2b-instruct |
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library_name: transformers |
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license: apache-2.0 |
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pipeline_tag: text-generation |
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tags: |
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- language |
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- granite-3.3 |
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- llama-cpp |
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- gguf-my-repo |
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inference: false |
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--- |
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# Triangle104/granite-3.3-2b-instruct-Q5_K_M-GGUF |
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This model was converted to GGUF format from [`ibm-granite/granite-3.3-2b-instruct`](https://huggingface.co/ibm-granite/granite-3.3-2b-instruct) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. |
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Refer to the [original model card](https://huggingface.co/ibm-granite/granite-3.3-2b-instruct) for more details on the model. |
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--- |
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Granite-3.3-2B-Instruct is a 2-billion parameter 128K context length language model fine-tuned for improved reasoning and instruction-following capabilities. Built on top of Granite-3.3-2B-Base, the model delivers significant gains on benchmarks for measuring generic performance including AlpacaEval-2.0 and Arena-Hard, and improvements in mathematics, coding, and instruction following. It supports structured reasoning through <think></think> and <response></response> tags, providing clear separation between internal thoughts and final outputs. The model has been trained on a carefully balanced combination of permissively licensed data and curated synthetic tasks. |
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--- |
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## Use with llama.cpp |
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Install llama.cpp through brew (works on Mac and Linux) |
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```bash |
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brew install llama.cpp |
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``` |
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Invoke the llama.cpp server or the CLI. |
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### CLI: |
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```bash |
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llama-cli --hf-repo Triangle104/granite-3.3-2b-instruct-Q5_K_M-GGUF --hf-file granite-3.3-2b-instruct-q5_k_m.gguf -p "The meaning to life and the universe is" |
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``` |
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### Server: |
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```bash |
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llama-server --hf-repo Triangle104/granite-3.3-2b-instruct-Q5_K_M-GGUF --hf-file granite-3.3-2b-instruct-q5_k_m.gguf -c 2048 |
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``` |
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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. |
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Step 1: Clone llama.cpp from GitHub. |
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``` |
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git clone https://github.com/ggerganov/llama.cpp |
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``` |
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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). |
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``` |
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cd llama.cpp && LLAMA_CURL=1 make |
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``` |
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Step 3: Run inference through the main binary. |
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``` |
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./llama-cli --hf-repo Triangle104/granite-3.3-2b-instruct-Q5_K_M-GGUF --hf-file granite-3.3-2b-instruct-q5_k_m.gguf -p "The meaning to life and the universe is" |
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``` |
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or |
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``` |
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./llama-server --hf-repo Triangle104/granite-3.3-2b-instruct-Q5_K_M-GGUF --hf-file granite-3.3-2b-instruct-q5_k_m.gguf -c 2048 |
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``` |
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