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metadata
license: apache-2.0
datasets:
  - argilla/distilabel-intel-orca-dpo-pairs
tags:
  - TensorBlock
  - GGUF
base_model: luqmanxyz/Maya_Hermes-2.5-Mistral-7B
model-index:
  - name: Maya_Hermes-2.5-Mistral-7B
    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: 66.3
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=luqmanxyz/Maya_Hermes-2.5-Mistral-7B
          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: 85.07
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=luqmanxyz/Maya_Hermes-2.5-Mistral-7B
          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: 63.23
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=luqmanxyz/Maya_Hermes-2.5-Mistral-7B
          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: 55.89
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=luqmanxyz/Maya_Hermes-2.5-Mistral-7B
          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: 78.85
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=luqmanxyz/Maya_Hermes-2.5-Mistral-7B
          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: 62.24
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=luqmanxyz/Maya_Hermes-2.5-Mistral-7B
          name: Open LLM Leaderboard
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luqmanxyz/Maya_Hermes-2.5-Mistral-7B - GGUF

This repo contains GGUF format model files for luqmanxyz/Maya_Hermes-2.5-Mistral-7B.

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
Maya_Hermes-2.5-Mistral-7B-Q2_K.gguf Q2_K 2.719 GB smallest, significant quality loss - not recommended for most purposes
Maya_Hermes-2.5-Mistral-7B-Q3_K_S.gguf Q3_K_S 3.165 GB very small, high quality loss
Maya_Hermes-2.5-Mistral-7B-Q3_K_M.gguf Q3_K_M 3.519 GB very small, high quality loss
Maya_Hermes-2.5-Mistral-7B-Q3_K_L.gguf Q3_K_L 3.822 GB small, substantial quality loss
Maya_Hermes-2.5-Mistral-7B-Q4_0.gguf Q4_0 4.109 GB legacy; small, very high quality loss - prefer using Q3_K_M
Maya_Hermes-2.5-Mistral-7B-Q4_K_S.gguf Q4_K_S 4.140 GB small, greater quality loss
Maya_Hermes-2.5-Mistral-7B-Q4_K_M.gguf Q4_K_M 4.368 GB medium, balanced quality - recommended
Maya_Hermes-2.5-Mistral-7B-Q5_0.gguf Q5_0 4.998 GB legacy; medium, balanced quality - prefer using Q4_K_M
Maya_Hermes-2.5-Mistral-7B-Q5_K_S.gguf Q5_K_S 4.998 GB large, low quality loss - recommended
Maya_Hermes-2.5-Mistral-7B-Q5_K_M.gguf Q5_K_M 5.131 GB large, very low quality loss - recommended
Maya_Hermes-2.5-Mistral-7B-Q6_K.gguf Q6_K 5.942 GB very large, extremely low quality loss
Maya_Hermes-2.5-Mistral-7B-Q8_0.gguf Q8_0 7.696 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/Maya_Hermes-2.5-Mistral-7B-GGUF --include "Maya_Hermes-2.5-Mistral-7B-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/Maya_Hermes-2.5-Mistral-7B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'