tensorblock/w4r10ck_SOLAR-10.7B-Instruct-v1.0-uncensored-GGUF

license: apache-2.0
tags:

• TensorBlock
• GGUF
  base_model: w4r10ck/SOLAR-10.7B-Instruct-v1.0-uncensored
  model-index:
• name: SOLAR-10.7B-Instruct-v1.0-uncensored
  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: 38.84
      name: strict accuracy
      source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=w4r10ck/SOLAR-10.7B-Instruct-v1.0-uncensored
      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: 33.86
      name: normalized accuracy
      source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=w4r10ck/SOLAR-10.7B-Instruct-v1.0-uncensored
      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: 0.23
      name: exact match
      source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=w4r10ck/SOLAR-10.7B-Instruct-v1.0-uncensored
      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: 5.93
      name: acc_norm
      source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=w4r10ck/SOLAR-10.7B-Instruct-v1.0-uncensored
      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: 18.49
      name: acc_norm
      source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=w4r10ck/SOLAR-10.7B-Instruct-v1.0-uncensored
      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: 26.04
      name: accuracy
      source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=w4r10ck/SOLAR-10.7B-Instruct-v1.0-uncensored
      name: Open LLM Leaderboard

w4r10ck/SOLAR-10.7B-Instruct-v1.0-uncensored - GGUF

This repo contains GGUF format model files for w4r10ck/SOLAR-10.7B-Instruct-v1.0-uncensored.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b5165.

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Prompt template

Unable to determine prompt format automatically. Please check the original model repository for the correct prompt format.

Model file specification

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/w4r10ck_SOLAR-10.7B-Instruct-v1.0-uncensored-GGUF --include "SOLAR-10.7B-Instruct-v1.0-uncensored-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/w4r10ck_SOLAR-10.7B-Instruct-v1.0-uncensored-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'