---
language:
- en
license: apache-2.0
library_name: transformers
tags:
- chat
- qwen
- qwen2
- finetune
- chatml
- OpenHermes-2.5
- HelpSteer2
- Orca
- SlimOrca
- TensorBlock
- GGUF
base_model: MaziyarPanahi/calme-2.4-qwen2-7b
datasets:
- nvidia/HelpSteer2
- teknium/OpenHermes-2.5
- microsoft/orca-math-word-problems-200k
- Open-Orca/SlimOrca
pipeline_tag: text-generation
inference: false
model_creator: MaziyarPanahi
quantized_by: MaziyarPanahi
model-index:
- name: calme-2.4-qwen2-7b
  results:
  - 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: 33.0
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.4-qwen2-7b
      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: 31.82
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.4-qwen2-7b
      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: 18.35
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.4-qwen2-7b
      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: 4.47
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.4-qwen2-7b
      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: 14.43
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.4-qwen2-7b
      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: 33.08
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.4-qwen2-7b
      name: Open LLM Leaderboard
---

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## MaziyarPanahi/calme-2.4-qwen2-7b - GGUF

This repo contains GGUF format model files for [MaziyarPanahi/calme-2.4-qwen2-7b](https://huggingface.co/MaziyarPanahi/calme-2.4-qwen2-7b).

The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).

## 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 |
| -------- | ---------- | --------- | ----------- |
| [calme-2.4-qwen2-7b-Q2_K.gguf](https://huggingface.co/tensorblock/calme-2.4-qwen2-7b-GGUF/tree/main/calme-2.4-qwen2-7b-Q2_K.gguf) | Q2_K | 2.809 GB | smallest, significant quality loss - not recommended for most purposes |
| [calme-2.4-qwen2-7b-Q3_K_S.gguf](https://huggingface.co/tensorblock/calme-2.4-qwen2-7b-GGUF/tree/main/calme-2.4-qwen2-7b-Q3_K_S.gguf) | Q3_K_S | 3.253 GB | very small, high quality loss |
| [calme-2.4-qwen2-7b-Q3_K_M.gguf](https://huggingface.co/tensorblock/calme-2.4-qwen2-7b-GGUF/tree/main/calme-2.4-qwen2-7b-Q3_K_M.gguf) | Q3_K_M | 3.547 GB | very small, high quality loss |
| [calme-2.4-qwen2-7b-Q3_K_L.gguf](https://huggingface.co/tensorblock/calme-2.4-qwen2-7b-GGUF/tree/main/calme-2.4-qwen2-7b-Q3_K_L.gguf) | Q3_K_L | 3.808 GB | small, substantial quality loss |
| [calme-2.4-qwen2-7b-Q4_0.gguf](https://huggingface.co/tensorblock/calme-2.4-qwen2-7b-GGUF/tree/main/calme-2.4-qwen2-7b-Q4_0.gguf) | Q4_0 | 4.127 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [calme-2.4-qwen2-7b-Q4_K_S.gguf](https://huggingface.co/tensorblock/calme-2.4-qwen2-7b-GGUF/tree/main/calme-2.4-qwen2-7b-Q4_K_S.gguf) | Q4_K_S | 4.152 GB | small, greater quality loss |
| [calme-2.4-qwen2-7b-Q4_K_M.gguf](https://huggingface.co/tensorblock/calme-2.4-qwen2-7b-GGUF/tree/main/calme-2.4-qwen2-7b-Q4_K_M.gguf) | Q4_K_M | 4.361 GB | medium, balanced quality - recommended |
| [calme-2.4-qwen2-7b-Q5_0.gguf](https://huggingface.co/tensorblock/calme-2.4-qwen2-7b-GGUF/tree/main/calme-2.4-qwen2-7b-Q5_0.gguf) | Q5_0 | 4.950 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [calme-2.4-qwen2-7b-Q5_K_S.gguf](https://huggingface.co/tensorblock/calme-2.4-qwen2-7b-GGUF/tree/main/calme-2.4-qwen2-7b-Q5_K_S.gguf) | Q5_K_S | 4.950 GB | large, low quality loss - recommended |
| [calme-2.4-qwen2-7b-Q5_K_M.gguf](https://huggingface.co/tensorblock/calme-2.4-qwen2-7b-GGUF/tree/main/calme-2.4-qwen2-7b-Q5_K_M.gguf) | Q5_K_M | 5.071 GB | large, very low quality loss - recommended |
| [calme-2.4-qwen2-7b-Q6_K.gguf](https://huggingface.co/tensorblock/calme-2.4-qwen2-7b-GGUF/tree/main/calme-2.4-qwen2-7b-Q6_K.gguf) | Q6_K | 5.825 GB | very large, extremely low quality loss |
| [calme-2.4-qwen2-7b-Q8_0.gguf](https://huggingface.co/tensorblock/calme-2.4-qwen2-7b-GGUF/tree/main/calme-2.4-qwen2-7b-Q8_0.gguf) | Q8_0 | 7.542 GB | very large, extremely low quality loss - not recommended |


## Downloading instruction

### Command line

Firstly, install Huggingface Client

```shell
pip install -U "huggingface_hub[cli]"
```

Then, downoad the individual model file the a local directory

```shell
huggingface-cli download tensorblock/calme-2.4-qwen2-7b-GGUF --include "calme-2.4-qwen2-7b-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:

```shell
huggingface-cli download tensorblock/calme-2.4-qwen2-7b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```