README.md

metadata

license: other
library_name: transformers
datasets:
  - vicgalle/alpaca-gpt4
extra_gated_heading: Access Gemma on Hugging Face
extra_gated_prompt: >-
  To access Gemma on Hugging Face, you’re required to review and agree to
  Google’s usage license. To do this, please ensure you’re logged-in to Hugging
  Face and click below. Requests are processed immediately.
extra_gated_button_content: Acknowledge license
license_name: gemma-terms-of-use
license_link: https://ai.google.dev/gemma/terms
base_model: mlabonne/Gemmalpaca-2B
tags:
  - TensorBlock
  - GGUF
model-index:
  - name: Gemmalpaca-2B
    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: 48.72
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Gemmalpaca-2B
          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: 71.36
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Gemmalpaca-2B
          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: 36.3
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Gemmalpaca-2B
          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: 41.24
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Gemmalpaca-2B
          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: 65.59
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Gemmalpaca-2B
          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: 10.69
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Gemmalpaca-2B
          name: Open LLM Leaderboard

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mlabonne/Gemmalpaca-2B - GGUF

This repo contains GGUF format model files for mlabonne/Gemmalpaca-2B.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.

Run them on the TensorBlock client using your local machine ↗

Prompt template

Model file specification

Filename	Quant type	File Size	Description
Gemmalpaca-2B-Q2_K.gguf	Q2_K	1.158 GB	smallest, significant quality loss - not recommended for most purposes
Gemmalpaca-2B-Q3_K_S.gguf	Q3_K_S	1.288 GB	very small, high quality loss
Gemmalpaca-2B-Q3_K_M.gguf	Q3_K_M	1.384 GB	very small, high quality loss
Gemmalpaca-2B-Q3_K_L.gguf	Q3_K_L	1.466 GB	small, substantial quality loss
Gemmalpaca-2B-Q4_0.gguf	Q4_0	1.551 GB	legacy; small, very high quality loss - prefer using Q3_K_M
Gemmalpaca-2B-Q4_K_S.gguf	Q4_K_S	1.560 GB	small, greater quality loss
Gemmalpaca-2B-Q4_K_M.gguf	Q4_K_M	1.630 GB	medium, balanced quality - recommended
Gemmalpaca-2B-Q5_0.gguf	Q5_0	1.799 GB	legacy; medium, balanced quality - prefer using Q4_K_M
Gemmalpaca-2B-Q5_K_S.gguf	Q5_K_S	1.799 GB	large, low quality loss - recommended
Gemmalpaca-2B-Q5_K_M.gguf	Q5_K_M	1.840 GB	large, very low quality loss - recommended
Gemmalpaca-2B-Q6_K.gguf	Q6_K	2.062 GB	very large, extremely low quality loss
Gemmalpaca-2B-Q8_0.gguf	Q8_0	2.669 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/Gemmalpaca-2B-GGUF --include "Gemmalpaca-2B-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/Gemmalpaca-2B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'