README.md

metadata

license: apache-2.0
language:
  - en
  - zh
base_model: prithivMLmods/Viper-Coder-HybridMini-v1.3
pipeline_tag: text-generation
library_name: transformers
tags:
  - text-generation-inference
  - trl
  - coder
  - 7B
  - TensorBlock
  - GGUF
model-index:
  - name: Viper-Coder-HybridMini-v1.3
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: IFEval (0-Shot)
          type: wis-k/instruction-following-eval
          split: train
          args:
            num_few_shot: 0
        metrics:
          - type: inst_level_strict_acc and prompt_level_strict_acc
            value: 61.04
            name: averaged accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=prithivMLmods%2FViper-Coder-HybridMini-v1.3
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: BBH (3-Shot)
          type: SaylorTwift/bbh
          split: test
          args:
            num_few_shot: 3
        metrics:
          - type: acc_norm
            value: 33.67
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=prithivMLmods%2FViper-Coder-HybridMini-v1.3
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MATH Lvl 5 (4-Shot)
          type: lighteval/MATH-Hard
          split: test
          args:
            num_few_shot: 4
        metrics:
          - type: exact_match
            value: 46.3
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=prithivMLmods%2FViper-Coder-HybridMini-v1.3
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GPQA (0-shot)
          type: Idavidrein/gpqa
          split: train
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 8.95
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=prithivMLmods%2FViper-Coder-HybridMini-v1.3
          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: 15.61
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=prithivMLmods%2FViper-Coder-HybridMini-v1.3
          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: 37.24
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=prithivMLmods%2FViper-Coder-HybridMini-v1.3
          name: Open LLM Leaderboard

prithivMLmods/Viper-Coder-HybridMini-v1.3 - GGUF

This repo contains GGUF format model files for prithivMLmods/Viper-Coder-HybridMini-v1.3.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4882.

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## 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
Viper-Coder-HybridMini-v1.3-Q2_K.gguf	Q2_K	3.016 GB	smallest, significant quality loss - not recommended for most purposes
Viper-Coder-HybridMini-v1.3-Q3_K_S.gguf	Q3_K_S	3.492 GB	very small, high quality loss
Viper-Coder-HybridMini-v1.3-Q3_K_M.gguf	Q3_K_M	3.808 GB	very small, high quality loss
Viper-Coder-HybridMini-v1.3-Q3_K_L.gguf	Q3_K_L	4.088 GB	small, substantial quality loss
Viper-Coder-HybridMini-v1.3-Q4_0.gguf	Q4_0	4.431 GB	legacy; small, very high quality loss - prefer using Q3_K_M
Viper-Coder-HybridMini-v1.3-Q4_K_S.gguf	Q4_K_S	4.458 GB	small, greater quality loss
Viper-Coder-HybridMini-v1.3-Q4_K_M.gguf	Q4_K_M	4.683 GB	medium, balanced quality - recommended
Viper-Coder-HybridMini-v1.3-Q5_0.gguf	Q5_0	5.315 GB	legacy; medium, balanced quality - prefer using Q4_K_M
Viper-Coder-HybridMini-v1.3-Q5_K_S.gguf	Q5_K_S	5.315 GB	large, low quality loss - recommended
Viper-Coder-HybridMini-v1.3-Q5_K_M.gguf	Q5_K_M	5.445 GB	large, very low quality loss - recommended
Viper-Coder-HybridMini-v1.3-Q6_K.gguf	Q6_K	6.254 GB	very large, extremely low quality loss
Viper-Coder-HybridMini-v1.3-Q8_0.gguf	Q8_0	8.099 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/Viper-Coder-HybridMini-v1.3-GGUF --include "Viper-Coder-HybridMini-v1.3-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/Viper-Coder-HybridMini-v1.3-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'