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Llama-3-70B-Orpo-v0.1-GGUF

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Llama-3-70B-Orpo-v0.1-GGUF / README.md
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metadata
language:
  - en
license: llama3
library_name: transformers
tags:
  - orpo
  - llama 3
  - rlhf
  - sft
  - TensorBlock
  - GGUF
base_model: dfurman/Llama-3-70B-Orpo-v0.1
datasets:
  - mlabonne/orpo-dpo-mix-40k
model-index:
  - name: Llama-3-70B-Orpo-v0.1
    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: 20.49
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/Llama-3-70B-Orpo-v0.1
          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: 24.09
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/Llama-3-70B-Orpo-v0.1
          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: 13.52
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/Llama-3-70B-Orpo-v0.1
          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: 1.01
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/Llama-3-70B-Orpo-v0.1
          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: 16.28
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/Llama-3-70B-Orpo-v0.1
          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: 32.14
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/Llama-3-70B-Orpo-v0.1
          name: Open LLM Leaderboard
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dfurman/Llama-3-70B-Orpo-v0.1 - GGUF

This repo contains GGUF format model files for dfurman/Llama-3-70B-Orpo-v0.1.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.

Prompt template 

<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

Model file specification

Filename Quant type File Size Description
Llama-3-70B-Orpo-v0.1-Q2_K.gguf Q2_K 26.375 GB smallest, significant quality loss - not recommended for most purposes
Llama-3-70B-Orpo-v0.1-Q3_K_S.gguf Q3_K_S 30.912 GB very small, high quality loss
Llama-3-70B-Orpo-v0.1-Q3_K_M.gguf Q3_K_M 34.268 GB very small, high quality loss
Llama-3-70B-Orpo-v0.1-Q3_K_L.gguf Q3_K_L 37.141 GB small, substantial quality loss
Llama-3-70B-Orpo-v0.1-Q4_0.gguf Q4_0 39.970 GB legacy; small, very high quality loss - prefer using Q3_K_M
Llama-3-70B-Orpo-v0.1-Q4_K_S.gguf Q4_K_S 40.347 GB small, greater quality loss
Llama-3-70B-Orpo-v0.1-Q4_K_M.gguf Q4_K_M 42.520 GB medium, balanced quality - recommended
Llama-3-70B-Orpo-v0.1-Q5_0.gguf Q5_0 48.657 GB legacy; medium, balanced quality - prefer using Q4_K_M
Llama-3-70B-Orpo-v0.1-Q5_K_S.gguf Q5_K_S 48.657 GB large, low quality loss - recommended
Llama-3-70B-Orpo-v0.1-Q5_K_M.gguf Q5_K_M 49.950 GB large, very low quality loss - recommended
Llama-3-70B-Orpo-v0.1-Q6_K Q6_K 57.888 GB very large, extremely low quality loss
Llama-3-70B-Orpo-v0.1-Q8_0 Q8_0 74.975 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/Llama-3-70B-Orpo-v0.1-GGUF --include "Llama-3-70B-Orpo-v0.1-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/Llama-3-70B-Orpo-v0.1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'