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| 1 | 
            +
            ---
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            base_model: ibm-granite/granite-8b-code-instruct-128k
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            datasets:
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            - bigcode/commitpackft
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            - TIGER-Lab/MathInstruct
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            - meta-math/MetaMathQA
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            +
            - glaiveai/glaive-code-assistant-v3
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            +
            - glaive-function-calling-v2
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            +
            - bugdaryan/sql-create-context-instruction
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            +
            - garage-bAInd/Open-Platypus
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            - nvidia/HelpSteer
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            - bigcode/self-oss-instruct-sc2-exec-filter-50k
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            library_name: transformers
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            license: apache-2.0
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            metrics:
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            +
            - code_eval
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            pipeline_tag: text-generation
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            tags:
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            - code
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            - granite
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            - llama-cpp
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            - gguf-my-repo
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            inference: false
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            model-index:
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            - name: granite-8B-Code-instruct-128k
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              results:
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              - task:
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                  type: text-generation
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                dataset:
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                  name: HumanEvalSynthesis (Python)
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                  type: bigcode/humanevalpack
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                metrics:
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                - type: pass@1
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                  value: 62.2
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                  name: pass@1
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                  verified: false
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                - type: pass@1
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                  value: 51.4
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                  name: pass@1
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                  verified: false
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                - type: pass@1
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                  value: 38.9
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                  name: pass@1
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                  verified: false
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                - type: pass@1
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                  value: 38.3
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                  name: pass@1
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                  verified: false
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              - task:
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                  type: text-generation
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                dataset:
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                  name: RepoQA (Python@16K)
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                  type: repoqa
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                metrics:
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                - type: pass@1 (thresh=0.5)
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                  value: 73.0
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                  name: pass@1 (thresh=0.5)
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                  verified: false
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                - type: pass@1 (thresh=0.5)
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                  value: 37.0
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                  name: pass@1 (thresh=0.5)
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                  verified: false
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                - type: pass@1 (thresh=0.5)
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                  value: 73.0
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                  name: pass@1 (thresh=0.5)
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                  verified: false
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            +
                - type: pass@1 (thresh=0.5)
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                  value: 62.0
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                  name: pass@1 (thresh=0.5)
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                  verified: false
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            +
                - type: pass@1 (thresh=0.5)
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            +
                  value: 63.0
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                  name: pass@1 (thresh=0.5)
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                  verified: false
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            ---
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            # TobDeBer/granite-8b-code-instruct-128k-Q4_K_M-GGUF
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            This model was converted to GGUF format from [`ibm-granite/granite-8b-code-instruct-128k`](https://huggingface.co/ibm-granite/granite-8b-code-instruct-128k) 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-8b-code-instruct-128k) for more details on the model.
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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 TobDeBer/granite-8b-code-instruct-128k-Q4_K_M-GGUF --hf-file granite-8b-code-instruct-128k-q4_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 TobDeBer/granite-8b-code-instruct-128k-Q4_K_M-GGUF --hf-file granite-8b-code-instruct-128k-q4_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 TobDeBer/granite-8b-code-instruct-128k-Q4_K_M-GGUF --hf-file granite-8b-code-instruct-128k-q4_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 TobDeBer/granite-8b-code-instruct-128k-Q4_K_M-GGUF --hf-file granite-8b-code-instruct-128k-q4_k_m.gguf -c 2048
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            ```
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