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metadata
language:
  - en
license: apache-2.0
library_name: transformers
tags:
  - transformers
  - llama-cpp
  - gguf-my-repo
base_model: openlm-research/open_llama_3b
datasets:
  - mwitiderrick/AlpacaCode
inference: true
model_type: llama
prompt_template: |
  ### Instruction:\n
  {prompt}
  ### Response:
created_by: mwitiderrick
pipeline_tag: text-generation
model-index:
  - name: mwitiderrick/open_llama_3b_instruct_v_0.2
    results:
      - task:
          type: text-generation
        dataset:
          name: hellaswag
          type: hellaswag
        metrics:
          - type: hellaswag (0-Shot)
            value: 0.6581
            name: hellaswag(0-Shot)
      - task:
          type: text-generation
        dataset:
          name: winogrande
          type: winogrande
        metrics:
          - type: winogrande (0-Shot)
            value: 0.6267
            name: winogrande(0-Shot)
      - task:
          type: text-generation
        dataset:
          name: arc_challenge
          type: arc_challenge
        metrics:
          - type: arc_challenge (0-Shot)
            value: 0.3712
            name: arc_challenge(0-Shot)
        source:
          url: https://huggingface.co./mwitiderrick/open_llama_3b_instruct_v_0.2
          name: open_llama_3b_instruct_v_0.2 model card

DavidAU/open_llama_3b_code_instruct_0.1-Q6_K-GGUF

This model was converted to GGUF format from mwitiderrick/open_llama_3b_code_instruct_0.1 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.

brew install ggerganov/ggerganov/llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo DavidAU/open_llama_3b_code_instruct_0.1-Q6_K-GGUF --model open_llama_3b_code_instruct_0.1.Q6_K.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo DavidAU/open_llama_3b_code_instruct_0.1-Q6_K-GGUF --model open_llama_3b_code_instruct_0.1.Q6_K.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

git clone https://github.com/ggerganov/llama.cpp &&             cd llama.cpp &&             make &&             ./main -m open_llama_3b_code_instruct_0.1.Q6_K.gguf -n 128