tensorblock/cognitivecomputations_WizardLM-33B-V1.0-Uncensored-GGUF

language:

• en
  license: other
  datasets:
• ehartford/WizardLM_evol_instruct_V2_196k_unfiltered_merged_split
  tags:
• TensorBlock
• GGUF
  base_model: cognitivecomputations/WizardLM-33B-V1.0-Uncensored
  model-index:
• name: WizardLM-33B-V1.0-Uncensored
  results:
  • task:
    type: text-generation
    name: Text Generation
    dataset:
    name: AI2 Reasoning Challenge (25-Shot)
    type: ai2_arc
    config: ARC-Challenge
    split: test
    args:
    num_few_shot: 25
    
    metrics:
    • type: acc_norm
      value: 63.65
      name: normalized accuracy
      source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ehartford/WizardLM-33B-V1.0-Uncensored
      name: Open LLM Leaderboard
  • task:
    type: text-generation
    name: Text Generation
    dataset:
    name: HellaSwag (10-Shot)
    type: hellaswag
    split: validation
    args:
    num_few_shot: 10
    
    metrics:
    • type: acc_norm
      value: 83.84
      name: normalized accuracy
      source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ehartford/WizardLM-33B-V1.0-Uncensored
      name: Open LLM Leaderboard
  • task:
    type: text-generation
    name: Text Generation
    dataset:
    name: MMLU (5-Shot)
    type: cais/mmlu
    config: all
    split: test
    args:
    num_few_shot: 5
    
    metrics:
    • type: acc
      value: 59.36
      name: accuracy
      source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ehartford/WizardLM-33B-V1.0-Uncensored
      name: Open LLM Leaderboard
  • task:
    type: text-generation
    name: Text Generation
    dataset:
    name: TruthfulQA (0-shot)
    type: truthful_qa
    config: multiple_choice
    split: validation
    args:
    num_few_shot: 0
    
    metrics:
    • type: mc2
      value: 56.8
      source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ehartford/WizardLM-33B-V1.0-Uncensored
      name: Open LLM Leaderboard
  • task:
    type: text-generation
    name: Text Generation
    dataset:
    name: Winogrande (5-shot)
    type: winogrande
    config: winogrande_xl
    split: validation
    args:
    num_few_shot: 5
    
    metrics:
    • type: acc
      value: 77.66
      name: accuracy
      source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ehartford/WizardLM-33B-V1.0-Uncensored
      name: Open LLM Leaderboard
  • task:
    type: text-generation
    name: Text Generation
    dataset:
    name: GSM8k (5-shot)
    type: gsm8k
    config: main
    split: test
    args:
    num_few_shot: 5
    
    metrics:
    • type: acc
      value: 18.65
      name: accuracy
      source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ehartford/WizardLM-33B-V1.0-Uncensored
      name: Open LLM Leaderboard

cognitivecomputations/WizardLM-33B-V1.0-Uncensored - GGUF

This repo contains GGUF format model files for cognitivecomputations/WizardLM-33B-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/cognitivecomputations_WizardLM-33B-V1.0-Uncensored-GGUF --include "WizardLM-33B-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/cognitivecomputations_WizardLM-33B-V1.0-Uncensored-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'