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Yi-34B-200K-AEZAKMI-v2-GGUF

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metadata
license: apache-2.0
tags:
  - llm
  - fine-tune
  - yi
  - TensorBlock
  - GGUF
datasets:
  - adamo1139/AEZAKMI_v2
license_name: yi-license
license_link: LICENSE
base_model: adamo1139/Yi-34B-200K-AEZAKMI-v2
model-index:
  - name: Yi-34B-200K-AEZAKMI-v2
    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: 67.92
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=adamo1139/Yi-34B-200K-AEZAKMI-v2
          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: 85.61
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=adamo1139/Yi-34B-200K-AEZAKMI-v2
          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: 75.22
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=adamo1139/Yi-34B-200K-AEZAKMI-v2
          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: 56.74
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=adamo1139/Yi-34B-200K-AEZAKMI-v2
          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: 81.61
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=adamo1139/Yi-34B-200K-AEZAKMI-v2
          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: 58.91
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=adamo1139/Yi-34B-200K-AEZAKMI-v2
          name: Open LLM Leaderboard
      - 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: 45.55
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=adamo1139/Yi-34B-200K-AEZAKMI-v2
          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: 35.28
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=adamo1139/Yi-34B-200K-AEZAKMI-v2
          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: 4.83
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=adamo1139/Yi-34B-200K-AEZAKMI-v2
          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: 10.96
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=adamo1139/Yi-34B-200K-AEZAKMI-v2
          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: 6.48
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=adamo1139/Yi-34B-200K-AEZAKMI-v2
          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: 39.03
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=adamo1139/Yi-34B-200K-AEZAKMI-v2
          name: Open LLM Leaderboard
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adamo1139/Yi-34B-200K-AEZAKMI-v2 - GGUF

This repo contains GGUF format model files for adamo1139/Yi-34B-200K-AEZAKMI-v2.

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
Yi-34B-200K-AEZAKMI-v2-Q2_K.gguf Q2_K 12.825 GB smallest, significant quality loss - not recommended for most purposes
Yi-34B-200K-AEZAKMI-v2-Q3_K_S.gguf Q3_K_S 14.960 GB very small, high quality loss
Yi-34B-200K-AEZAKMI-v2-Q3_K_M.gguf Q3_K_M 16.655 GB very small, high quality loss
Yi-34B-200K-AEZAKMI-v2-Q3_K_L.gguf Q3_K_L 18.139 GB small, substantial quality loss
Yi-34B-200K-AEZAKMI-v2-Q4_0.gguf Q4_0 19.467 GB legacy; small, very high quality loss - prefer using Q3_K_M
Yi-34B-200K-AEZAKMI-v2-Q4_K_S.gguf Q4_K_S 19.599 GB small, greater quality loss
Yi-34B-200K-AEZAKMI-v2-Q4_K_M.gguf Q4_K_M 20.659 GB medium, balanced quality - recommended
Yi-34B-200K-AEZAKMI-v2-Q5_0.gguf Q5_0 23.708 GB legacy; medium, balanced quality - prefer using Q4_K_M
Yi-34B-200K-AEZAKMI-v2-Q5_K_S.gguf Q5_K_S 23.708 GB large, low quality loss - recommended
Yi-34B-200K-AEZAKMI-v2-Q5_K_M.gguf Q5_K_M 24.322 GB large, very low quality loss - recommended
Yi-34B-200K-AEZAKMI-v2-Q6_K.gguf Q6_K 28.214 GB very large, extremely low quality loss
Yi-34B-200K-AEZAKMI-v2-Q8_0.gguf Q8_0 36.542 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/Yi-34B-200K-AEZAKMI-v2-GGUF --include "Yi-34B-200K-AEZAKMI-v2-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/Yi-34B-200K-AEZAKMI-v2-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'