README.md

metadata

language:
  - nl
license: cc-by-nc-4.0
library_name: transformers
tags:
  - trl
  - dpo
  - conversational
  - TensorBlock
  - GGUF
datasets:
  - BramVanroy/ultra_feedback_dutch_cleaned
pipeline_tag: text-generation
inference: false
base_model: robinsmits/Qwen1.5-7B-Dutch-Chat
model-index:
  - name: Qwen1.5-7B-Dutch-Chat
    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: 53.92
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=robinsmits/Qwen1.5-7B-Dutch-Chat
          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: 76.03
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=robinsmits/Qwen1.5-7B-Dutch-Chat
          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: 62.38
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=robinsmits/Qwen1.5-7B-Dutch-Chat
          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: 45.34
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=robinsmits/Qwen1.5-7B-Dutch-Chat
          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: 68.82
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=robinsmits/Qwen1.5-7B-Dutch-Chat
          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: 15.47
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=robinsmits/Qwen1.5-7B-Dutch-Chat
          name: Open LLM Leaderboard

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

robinsmits/Qwen1.5-7B-Dutch-Chat - GGUF

This repo contains GGUF format model files for robinsmits/Qwen1.5-7B-Dutch-Chat.

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

<|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
Qwen1.5-7B-Dutch-Chat-Q2_K.gguf	Q2_K	3.102 GB	smallest, significant quality loss - not recommended for most purposes
Qwen1.5-7B-Dutch-Chat-Q3_K_S.gguf	Q3_K_S	3.568 GB	very small, high quality loss
Qwen1.5-7B-Dutch-Chat-Q3_K_M.gguf	Q3_K_M	3.917 GB	very small, high quality loss
Qwen1.5-7B-Dutch-Chat-Q3_K_L.gguf	Q3_K_L	4.216 GB	small, substantial quality loss
Qwen1.5-7B-Dutch-Chat-Q4_0.gguf	Q4_0	4.510 GB	legacy; small, very high quality loss - prefer using Q3_K_M
Qwen1.5-7B-Dutch-Chat-Q4_K_S.gguf	Q4_K_S	4.541 GB	small, greater quality loss
Qwen1.5-7B-Dutch-Chat-Q4_K_M.gguf	Q4_K_M	4.765 GB	medium, balanced quality - recommended
Qwen1.5-7B-Dutch-Chat-Q5_0.gguf	Q5_0	5.397 GB	legacy; medium, balanced quality - prefer using Q4_K_M
Qwen1.5-7B-Dutch-Chat-Q5_K_S.gguf	Q5_K_S	5.397 GB	large, low quality loss - recommended
Qwen1.5-7B-Dutch-Chat-Q5_K_M.gguf	Q5_K_M	5.529 GB	large, very low quality loss - recommended
Qwen1.5-7B-Dutch-Chat-Q6_K.gguf	Q6_K	6.340 GB	very large, extremely low quality loss
Qwen1.5-7B-Dutch-Chat-Q8_0.gguf	Q8_0	8.209 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/Qwen1.5-7B-Dutch-Chat-GGUF --include "Qwen1.5-7B-Dutch-Chat-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/Qwen1.5-7B-Dutch-Chat-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'