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--- |
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pipeline_tag: text-generation |
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inference: false |
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license: apache-2.0 |
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library_name: transformers |
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tags: |
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- language |
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- granite-3.0 |
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- llama-cpp |
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- gguf-my-repo |
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base_model: ibm-granite/granite-3.0-8b-instruct |
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model-index: |
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- name: granite-3.0-2b-instruct |
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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: IFEval |
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type: instruction-following |
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metrics: |
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- type: pass@1 |
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value: 52.27 |
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name: pass@1 |
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- type: pass@1 |
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value: 8.22 |
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name: pass@1 |
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- task: |
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type: text-generation |
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dataset: |
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name: AGI-Eval |
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type: human-exams |
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metrics: |
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- type: pass@1 |
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value: 40.52 |
|
name: pass@1 |
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- type: pass@1 |
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value: 65.82 |
|
name: pass@1 |
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- type: pass@1 |
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value: 34.45 |
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name: pass@1 |
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- task: |
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type: text-generation |
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dataset: |
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name: OBQA |
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type: commonsense |
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metrics: |
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- type: pass@1 |
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value: 46.6 |
|
name: pass@1 |
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- type: pass@1 |
|
value: 71.21 |
|
name: pass@1 |
|
- type: pass@1 |
|
value: 82.61 |
|
name: pass@1 |
|
- type: pass@1 |
|
value: 77.51 |
|
name: pass@1 |
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- type: pass@1 |
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value: 60.32 |
|
name: pass@1 |
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- task: |
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type: text-generation |
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dataset: |
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name: BoolQ |
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type: reading-comprehension |
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metrics: |
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- type: pass@1 |
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value: 88.65 |
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name: pass@1 |
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- type: pass@1 |
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value: 21.58 |
|
name: pass@1 |
|
- task: |
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type: text-generation |
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dataset: |
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name: ARC-C |
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type: reasoning |
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metrics: |
|
- type: pass@1 |
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value: 64.16 |
|
name: pass@1 |
|
- type: pass@1 |
|
value: 33.81 |
|
name: pass@1 |
|
- type: pass@1 |
|
value: 51.55 |
|
name: pass@1 |
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- task: |
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type: text-generation |
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dataset: |
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name: HumanEvalSynthesis |
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type: code |
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metrics: |
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- type: pass@1 |
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value: 64.63 |
|
name: pass@1 |
|
- type: pass@1 |
|
value: 57.16 |
|
name: pass@1 |
|
- type: pass@1 |
|
value: 65.85 |
|
name: pass@1 |
|
- type: pass@1 |
|
value: 49.6 |
|
name: pass@1 |
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- task: |
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type: text-generation |
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dataset: |
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name: GSM8K |
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type: math |
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metrics: |
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- type: pass@1 |
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value: 68.99 |
|
name: pass@1 |
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- type: pass@1 |
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value: 30.94 |
|
name: pass@1 |
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- task: |
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type: text-generation |
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dataset: |
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name: PAWS-X (7 langs) |
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type: multilingual |
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metrics: |
|
- type: pass@1 |
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value: 64.94 |
|
name: pass@1 |
|
- type: pass@1 |
|
value: 48.2 |
|
name: pass@1 |
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--- |
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|
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# aashish1904/granite-3.0-8b-instruct-Q2_K-GGUF |
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This model was converted to GGUF format from [`ibm-granite/granite-3.0-8b-instruct`](https://huggingface.co/ibm-granite/granite-3.0-8b-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-3.0-8b-instruct) for more details on the model. |
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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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|
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```bash |
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brew install llama.cpp |
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|
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``` |
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Invoke the llama.cpp server or the CLI. |
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|
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### CLI: |
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```bash |
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llama-cli --hf-repo aashish1904/granite-3.0-8b-instruct-Q2_K-GGUF --hf-file granite-3.0-8b-instruct-q2_k.gguf -p "The meaning to life and the universe is" |
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``` |
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|
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### Server: |
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```bash |
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llama-server --hf-repo aashish1904/granite-3.0-8b-instruct-Q2_K-GGUF --hf-file granite-3.0-8b-instruct-q2_k.gguf -c 2048 |
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``` |
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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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|
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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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|
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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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|
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Step 3: Run inference through the main binary. |
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``` |
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./llama-cli --hf-repo aashish1904/granite-3.0-8b-instruct-Q2_K-GGUF --hf-file granite-3.0-8b-instruct-q2_k.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 aashish1904/granite-3.0-8b-instruct-Q2_K-GGUF --hf-file granite-3.0-8b-instruct-q2_k.gguf -c 2048 |
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``` |
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|
