README.md

metadata

license: cc-by-nc-4.0
language:
  - en
  - de
  - fr
  - zh
  - pt
  - nl
  - ru
  - ko
  - it
  - es
metrics:
  - comet
pipeline_tag: translation
base_model: Unbabel/TowerBase-7B-v0.1
tags:
  - TensorBlock
  - GGUF
model-index:
  - name: TowerBase-7B-v0.1
    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: 51.02
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Unbabel/TowerBase-7B-v0.1
          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: 77.68
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Unbabel/TowerBase-7B-v0.1
          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: 43.48
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Unbabel/TowerBase-7B-v0.1
          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: 37.29
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Unbabel/TowerBase-7B-v0.1
          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: 72.06
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Unbabel/TowerBase-7B-v0.1
          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: 13.12
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Unbabel/TowerBase-7B-v0.1
          name: Open LLM Leaderboard

Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server

Unbabel/TowerBase-7B-v0.1 - GGUF

This repo contains GGUF format model files for Unbabel/TowerBase-7B-v0.1.

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
TowerBase-7B-v0.1-Q2_K.gguf	Q2_K	2.359 GB	smallest, significant quality loss - not recommended for most purposes
TowerBase-7B-v0.1-Q3_K_S.gguf	Q3_K_S	2.746 GB	very small, high quality loss
TowerBase-7B-v0.1-Q3_K_M.gguf	Q3_K_M	3.072 GB	very small, high quality loss
TowerBase-7B-v0.1-Q3_K_L.gguf	Q3_K_L	3.350 GB	small, substantial quality loss
TowerBase-7B-v0.1-Q4_0.gguf	Q4_0	3.563 GB	legacy; small, very high quality loss - prefer using Q3_K_M
TowerBase-7B-v0.1-Q4_K_S.gguf	Q4_K_S	3.592 GB	small, greater quality loss
TowerBase-7B-v0.1-Q4_K_M.gguf	Q4_K_M	3.801 GB	medium, balanced quality - recommended
TowerBase-7B-v0.1-Q5_0.gguf	Q5_0	4.332 GB	legacy; medium, balanced quality - prefer using Q4_K_M
TowerBase-7B-v0.1-Q5_K_S.gguf	Q5_K_S	4.332 GB	large, low quality loss - recommended
TowerBase-7B-v0.1-Q5_K_M.gguf	Q5_K_M	4.455 GB	large, very low quality loss - recommended
TowerBase-7B-v0.1-Q6_K.gguf	Q6_K	5.149 GB	very large, extremely low quality loss
TowerBase-7B-v0.1-Q8_0.gguf	Q8_0	6.669 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/TowerBase-7B-v0.1-GGUF --include "TowerBase-7B-v0.1-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/TowerBase-7B-v0.1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'