Transformers
	
	
	
	
	GGUF
	
	
	
		
	
	mergekit
	
	
	
		
	
	
		Merge
	
	
	
	
	shining-valiant
	
	
	
	
	shining-valiant-2
	
	
	
	
	enigma
	
	
	
	
	plum
	
	
	
	
	plumcode
	
	
	
	
	code
	
	
	
	
	valiant
	
	
	
	
	valiant-labs
	
	
	
	
	llama
	
	
	
	
	llama-3.1
	
	
	
	
	llama-3.1-instruct
	
	
	
	
	llama-3.1-instruct-8b
	
	
	
	
	llama-3
	
	
	
	
	llama-3-instruct
	
	
	
	
	llama-3-instruct-8b
	
	
	
	
	8b
	
	
	
	
	code-instruct
	
	
	
	
	python
	
	
	
	
	science
	
	
	
	
	physics
	
	
	
	
	biology
	
	
	
	
	chemistry
	
	
	
	
	compsci
	
	
	
	
	computer-science
	
	
	
	
	engineering
	
	
	
	
	technical
	
	
	
	
	conversational
	
	
	
	
	chat
	
	
	
	
	instruct
	
	
	
	
	llama-cpp
	
	
	
	
	gguf-my-repo
	
	
	
		
	
	
		Eval Results
	
	
metadata
			library_name: transformers
license: llama3.1
tags:
  - mergekit
  - merge
  - shining-valiant
  - shining-valiant-2
  - enigma
  - plum
  - plumcode
  - code
  - valiant
  - valiant-labs
  - llama
  - llama-3.1
  - llama-3.1-instruct
  - llama-3.1-instruct-8b
  - llama-3
  - llama-3-instruct
  - llama-3-instruct-8b
  - 8b
  - code-instruct
  - python
  - science
  - physics
  - biology
  - chemistry
  - compsci
  - computer-science
  - engineering
  - technical
  - conversational
  - chat
  - instruct
  - llama-cpp
  - gguf-my-repo
base_model: sequelbox/Llama3.1-8B-PlumCode
model-index:
  - name: Llama3.1-8B-PlumCode
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: Winogrande (5-Shot)
          type: Winogrande
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 73.16
            name: acc
      - 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: 20.45
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode
          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: 8.5
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode
          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: 2.42
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode
          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: 3.47
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode
          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: 8.97
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode
          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: 14.84
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode
          name: Open LLM Leaderboard
Triangle104/Llama3.1-8B-PlumCode-Q8_0-GGUF
This model was converted to GGUF format from sequelbox/Llama3.1-8B-PlumCode 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 Triangle104/Llama3.1-8B-PlumCode-Q8_0-GGUF --hf-file llama3.1-8b-plumcode-q8_0.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo Triangle104/Llama3.1-8B-PlumCode-Q8_0-GGUF --hf-file llama3.1-8b-plumcode-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 Triangle104/Llama3.1-8B-PlumCode-Q8_0-GGUF --hf-file llama3.1-8b-plumcode-q8_0.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo Triangle104/Llama3.1-8B-PlumCode-Q8_0-GGUF --hf-file llama3.1-8b-plumcode-q8_0.gguf -c 2048
