README.md

metadata

language:
  - en
license: llama3.2
library_name: transformers
base_model: Nexesenex/meditsolutions_Llama-3.2-SUN-1B-Instruct
datasets:
  - argilla/OpenHermesPreferences
  - argilla/magpie-ultra-v0.1
  - argilla/Capybara-Preferences-Filtered
  - mlabonne/open-perfectblend
  - HuggingFaceTB/everyday-conversations-llama3.1-2k
  - WizardLMTeam/WizardLM_evol_instruct_V2_196k
  - ProlificAI/social-reasoning-rlhf
  - allenai/tulu-3-sft-mixture
  - allenai/llama-3.1-tulu-3-8b-preference-mixture
pipeline_tag: text-generation
tags:
  - llama-cpp
  - gguf-my-repo
model-index:
  - name: Llama-3.2-SUN-1B-Instruct
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: IFEval (0-Shot)
          type: HuggingFaceH4/ifeval
          args:
            num_few_shot: 0
        metrics:
          - type: inst_level_strict_acc and prompt_level_strict_acc
            value: 64.13
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=meditsolutions/Llama-3.2-SUN-1B-Instruct
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: BBH (3-Shot)
          type: BBH
          args:
            num_few_shot: 3
        metrics:
          - type: acc_norm
            value: 9.18
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=meditsolutions/Llama-3.2-SUN-1B-Instruct
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MATH Lvl 5 (4-Shot)
          type: hendrycks/competition_math
          args:
            num_few_shot: 4
        metrics:
          - type: exact_match
            value: 4.61
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=meditsolutions/Llama-3.2-SUN-1B-Instruct
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GPQA (0-shot)
          type: Idavidrein/gpqa
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 0
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=meditsolutions/Llama-3.2-SUN-1B-Instruct
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MuSR (0-shot)
          type: TAUR-Lab/MuSR
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 4.05
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=meditsolutions/Llama-3.2-SUN-1B-Instruct
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MMLU-PRO (5-shot)
          type: TIGER-Lab/MMLU-Pro
          config: main
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 8.68
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=meditsolutions/Llama-3.2-SUN-1B-Instruct
          name: Open LLM Leaderboard

Nexesenex/meditsolutions_Llama-3.2-SUN-1B-Instruct-GGUF

This model was converted to GGUF format from Nexesenex/meditsolutions_Llama-3.2-SUN-1B-Instruct using croco.cpp's fork Croco.cpp via the ggml.ai's GGUF-my-repo space. This model was converted to GGUF format from Nexesenex/meditsolutions_Llama-3.2-SUN-1B-Instruct using llama.cpp's fork Croco.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 Nexesenex/meditsolutions_Llama-3.2-SUN-1B-Instruct-GGUF --hf-file meditsolutions_llama-3.2-sun-1b-instruct-q8_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Nexesenex/meditsolutions_Llama-3.2-SUN-1B-Instruct-GGUF --hf-file meditsolutions_llama-3.2-sun-1b-instruct-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. -> necessary to use Croco.

Step 1: Clone llama.cpp from GitHub. -> necessary to use Croco.

git clone https://github.com/Nexesenex/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 Nexesenex/meditsolutions_Llama-3.2-SUN-1B-Instruct-GGUF --hf-file meditsolutions_llama-3.2-sun-1b-instruct-q8_0.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Nexesenex/meditsolutions_Llama-3.2-SUN-1B-Instruct-GGUF --hf-file meditsolutions_llama-3.2-sun-1b-instruct-q8_0.gguf -c 2048