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granite-3.0-1b-a400m-instruct-GGUF

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metadata
pipeline_tag: text-generation
inference: false
license: apache-2.0
library_name: transformers
tags:
  - language
  - granite-3.0
  - TensorBlock
  - GGUF
base_model: ibm-granite/granite-3.0-1b-a400m-instruct
model-index:
  - name: granite-3.0-2b-instruct
    results:
      - task:
          type: text-generation
        dataset:
          name: IFEval
          type: instruction-following
        metrics:
          - type: pass@1
            value: 32.39
            name: pass@1
          - type: pass@1
            value: 6.17
            name: pass@1
      - task:
          type: text-generation
        dataset:
          name: AGI-Eval
          type: human-exams
        metrics:
          - type: pass@1
            value: 20.35
            name: pass@1
          - type: pass@1
            value: 32
            name: pass@1
          - type: pass@1
            value: 12.21
            name: pass@1
      - task:
          type: text-generation
        dataset:
          name: OBQA
          type: commonsense
        metrics:
          - type: pass@1
            value: 38.4
            name: pass@1
          - type: pass@1
            value: 47.55
            name: pass@1
          - type: pass@1
            value: 65.59
            name: pass@1
          - type: pass@1
            value: 61.17
            name: pass@1
          - type: pass@1
            value: 49.11
            name: pass@1
      - task:
          type: text-generation
        dataset:
          name: BoolQ
          type: reading-comprehension
        metrics:
          - type: pass@1
            value: 70.12
            name: pass@1
          - type: pass@1
            value: 1.27
            name: pass@1
      - task:
          type: text-generation
        dataset:
          name: ARC-C
          type: reasoning
        metrics:
          - type: pass@1
            value: 41.21
            name: pass@1
          - type: pass@1
            value: 23.07
            name: pass@1
          - type: pass@1
            value: 31.77
            name: pass@1
      - task:
          type: text-generation
        dataset:
          name: HumanEvalSynthesis
          type: code
        metrics:
          - type: pass@1
            value: 30.18
            name: pass@1
          - type: pass@1
            value: 26.22
            name: pass@1
          - type: pass@1
            value: 21.95
            name: pass@1
          - type: pass@1
            value: 15.4
            name: pass@1
      - task:
          type: text-generation
        dataset:
          name: GSM8K
          type: math
        metrics:
          - type: pass@1
            value: 26.31
            name: pass@1
          - type: pass@1
            value: 10.88
            name: pass@1
      - task:
          type: text-generation
        dataset:
          name: PAWS-X (7 langs)
          type: multilingual
        metrics:
          - type: pass@1
            value: 45.84
            name: pass@1
          - type: pass@1
            value: 11.8
            name: pass@1
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ibm-granite/granite-3.0-1b-a400m-instruct - GGUF

This repo contains GGUF format model files for ibm-granite/granite-3.0-1b-a400m-instruct.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.

Prompt template 

<|start_of_role|>system<|end_of_role|>{system_prompt}<|end_of_text|>
<|start_of_role|>user<|end_of_role|>{prompt}<|end_of_text|>
<|start_of_role|>assistant<|end_of_role|>

Model file specification

Filename Quant type File Size Description
granite-3.0-1b-a400m-instruct-Q2_K.gguf Q2_K 0.512 GB smallest, significant quality loss - not recommended for most purposes
granite-3.0-1b-a400m-instruct-Q3_K_S.gguf Q3_K_S 0.598 GB very small, high quality loss
granite-3.0-1b-a400m-instruct-Q3_K_M.gguf Q3_K_M 0.659 GB very small, high quality loss
granite-3.0-1b-a400m-instruct-Q3_K_L.gguf Q3_K_L 0.711 GB small, substantial quality loss
granite-3.0-1b-a400m-instruct-Q4_0.gguf Q4_0 0.768 GB legacy; small, very high quality loss - prefer using Q3_K_M
granite-3.0-1b-a400m-instruct-Q4_K_S.gguf Q4_K_S 0.775 GB small, greater quality loss
granite-3.0-1b-a400m-instruct-Q4_K_M.gguf Q4_K_M 0.822 GB medium, balanced quality - recommended
granite-3.0-1b-a400m-instruct-Q5_0.gguf Q5_0 0.929 GB legacy; medium, balanced quality - prefer using Q4_K_M
granite-3.0-1b-a400m-instruct-Q5_K_S.gguf Q5_K_S 0.929 GB large, low quality loss - recommended
granite-3.0-1b-a400m-instruct-Q5_K_M.gguf Q5_K_M 0.956 GB large, very low quality loss - recommended
granite-3.0-1b-a400m-instruct-Q6_K.gguf Q6_K 1.099 GB very large, extremely low quality loss
granite-3.0-1b-a400m-instruct-Q8_0.gguf Q8_0 1.422 GB very large, extremely low quality loss - not recommended

Downloading instruction

Command line

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/granite-3.0-1b-a400m-instruct-GGUF --include "granite-3.0-1b-a400m-instruct-Q2_K.gguf" --local-dir MY_LOCAL_DIR

If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:

huggingface-cli download tensorblock/granite-3.0-1b-a400m-instruct-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'