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metadata
language:
  - en
license: apache-2.0
library_name: transformers
datasets:
  - WizardLM/WizardLM_evol_instruct_V2_196k
tags:
  - TensorBlock
  - GGUF
base_model: harborwater/open-llama-3b-v2-wizard-evol-instuct-v2-196k
model-index:
  - name: open-llama-3b-v2-wizard-evol-instuct-v2-196k
    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: 41.81
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=harborwater/open-llama-3b-v2-wizard-evol-instuct-v2-196k
          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: 73.01
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=harborwater/open-llama-3b-v2-wizard-evol-instuct-v2-196k
          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: 26.36
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=harborwater/open-llama-3b-v2-wizard-evol-instuct-v2-196k
          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: 38.99
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=harborwater/open-llama-3b-v2-wizard-evol-instuct-v2-196k
          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: 66.69
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=harborwater/open-llama-3b-v2-wizard-evol-instuct-v2-196k
          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: 1.9
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=harborwater/open-llama-3b-v2-wizard-evol-instuct-v2-196k
          name: Open LLM Leaderboard
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harborwater/open-llama-3b-v2-wizard-evol-instuct-v2-196k - GGUF

This repo contains GGUF format model files for harborwater/open-llama-3b-v2-wizard-evol-instuct-v2-196k.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.

Prompt template


Model file specification

Filename Quant type File Size Description
open-llama-3b-v2-wizard-evol-instuct-v2-196k-Q2_K.gguf Q2_K 1.844 GB smallest, significant quality loss - not recommended for most purposes
open-llama-3b-v2-wizard-evol-instuct-v2-196k-Q3_K_S.gguf Q3_K_S 1.844 GB very small, high quality loss
open-llama-3b-v2-wizard-evol-instuct-v2-196k-Q3_K_M.gguf Q3_K_M 1.992 GB very small, high quality loss
open-llama-3b-v2-wizard-evol-instuct-v2-196k-Q3_K_L.gguf Q3_K_L 2.062 GB small, substantial quality loss
open-llama-3b-v2-wizard-evol-instuct-v2-196k-Q4_0.gguf Q4_0 1.844 GB legacy; small, very high quality loss - prefer using Q3_K_M
open-llama-3b-v2-wizard-evol-instuct-v2-196k-Q4_K_S.gguf Q4_K_S 2.238 GB small, greater quality loss
open-llama-3b-v2-wizard-evol-instuct-v2-196k-Q4_K_M.gguf Q4_K_M 2.403 GB medium, balanced quality - recommended
open-llama-3b-v2-wizard-evol-instuct-v2-196k-Q5_0.gguf Q5_0 2.231 GB legacy; medium, balanced quality - prefer using Q4_K_M
open-llama-3b-v2-wizard-evol-instuct-v2-196k-Q5_K_S.gguf Q5_K_S 2.424 GB large, low quality loss - recommended
open-llama-3b-v2-wizard-evol-instuct-v2-196k-Q5_K_M.gguf Q5_K_M 2.568 GB large, very low quality loss - recommended
open-llama-3b-v2-wizard-evol-instuct-v2-196k-Q6_K.gguf Q6_K 3.392 GB very large, extremely low quality loss
open-llama-3b-v2-wizard-evol-instuct-v2-196k-Q8_0.gguf Q8_0 3.392 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/open-llama-3b-v2-wizard-evol-instuct-v2-196k-GGUF --include "open-llama-3b-v2-wizard-evol-instuct-v2-196k-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/open-llama-3b-v2-wizard-evol-instuct-v2-196k-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'