metadata

language:
  - en
  - ko
library_name: transformers
license: cc-by-nc-4.0
pipeline_tag: text-generation
model_id: kakaocorp/kanana-nano-2.1b-base
repo: kakaocorp/kanana-nano-2.1b-base
developers: Kanana LLM
training_regime: bf16 mixed precision
tags:
  - llama-cpp
  - gguf-my-repo
base_model: kakaocorp/kanana-nano-2.1b-base
model-index:
  - name: kanana-nano-2.1b-base
    results:
      - task:
          type: multiple_choice
          name: mmlu
        dataset:
          name: mmlu (5-shots)
          type: hails/mmlu_no_train
        metrics:
          - type: acc
            value: 54.83
            name: acc
      - task:
          type: generate_until
          name: kmmlu
        dataset:
          name: kmmlu-direct (5-shots)
          type: HAERAE-HUB/KMMLU
        metrics:
          - type: exact_match
            value: 44.83
            name: exact_match
      - task:
          type: multiple_choice
          name: haerae
        dataset:
          name: haerae (5-shots)
          type: HAERAE-HUB/HAE_RAE_BENCH
        metrics:
          - type: acc_norm
            value: 77.09
            name: acc_norm
      - task:
          type: generate_until
          name: gsm8k
        dataset:
          name: gsm8k (5-shots)
          type: openai/gsm8k
        metrics:
          - type: exact_match
            value: 46.32
            name: exact_match_strict
      - task:
          type: generate_until
          name: humaneval
        dataset:
          name: humaneval (0-shots)
          type: openai/openai_humaneval
        metrics:
          - type: pass@1
            value: 31.1
            name: pass@1
      - task:
          type: generate_until
          name: mbpp
        dataset:
          name: mbpp (3-shots)
          type: google-research-datasets/mbpp
        metrics:
          - type: pass@1
            value: 46.2
            name: pass@1

nonemonehpark/kanana-nano-2.1b-base-Q8_0-GGUF

This model was converted to GGUF format from kakaocorp/kanana-nano-2.1b-base using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo nonemonehpark/kanana-nano-2.1b-base-Q8_0-GGUF --hf-file kanana-nano-2.1b-base-q8_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo nonemonehpark/kanana-nano-2.1b-base-Q8_0-GGUF --hf-file kanana-nano-2.1b-base-q8_0.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps 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 nonemonehpark/kanana-nano-2.1b-base-Q8_0-GGUF --hf-file kanana-nano-2.1b-base-q8_0.gguf -p "The meaning to life and the universe is"

./llama-server --hf-repo nonemonehpark/kanana-nano-2.1b-base-Q8_0-GGUF --hf-file kanana-nano-2.1b-base-q8_0.gguf -c 2048