---
language:
- en
license: other
tags:
- axolotl
- instruct
- finetune
- chatml
- gpt4
- synthetic data
- science
- physics
- chemistry
- biology
- math
- qwen
- qwen2
- TensorBlock
- GGUF
base_model: Weyaxi/Einstein-v7-Qwen2-7B
datasets:
- allenai/ai2_arc
- camel-ai/physics
- camel-ai/chemistry
- camel-ai/biology
- camel-ai/math
- metaeval/reclor
- openbookqa
- mandyyyyii/scibench
- derek-thomas/ScienceQA
- TIGER-Lab/ScienceEval
- jondurbin/airoboros-3.2
- LDJnr/Capybara
- Cot-Alpaca-GPT4-From-OpenHermes-2.5
- STEM-AI-mtl/Electrical-engineering
- knowrohit07/saraswati-stem
- sablo/oasst2_curated
- lmsys/lmsys-chat-1m
- TIGER-Lab/MathInstruct
- bigbio/med_qa
- meta-math/MetaMathQA-40K
- openbookqa
- piqa
- metaeval/reclor
- derek-thomas/ScienceQA
- scibench
- sciq
- Open-Orca/SlimOrca
- migtissera/Synthia-v1.3
- TIGER-Lab/ScienceEval
- allenai/WildChat
- microsoft/orca-math-word-problems-200k
- openchat/openchat_sharegpt4_dataset
- teknium/GPTeacher-General-Instruct
- m-a-p/CodeFeedback-Filtered-Instruction
- totally-not-an-llm/EverythingLM-data-V3
- HuggingFaceH4/no_robots
- OpenAssistant/oasst_top1_2023-08-25
- WizardLM/WizardLM_evol_instruct_70k
- abacusai/SystemChat-1.1
- H-D-T/Buzz-V1.2
model-index:
- name: Einstein-v7-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: 41.0
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Weyaxi/Einstein-v7-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: 32.84
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Weyaxi/Einstein-v7-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: 15.18
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Weyaxi/Einstein-v7-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: 6.6
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Weyaxi/Einstein-v7-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: 14.06
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Weyaxi/Einstein-v7-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: 34.4
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Weyaxi/Einstein-v7-Qwen2-7B
      name: Open LLM Leaderboard
---

<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<div style="display: flex; justify-content: space-between; width: 100%;">
    <div style="display: flex; flex-direction: column; align-items: flex-start;">
        <p style="margin-top: 0.5em; margin-bottom: 0em;">
            Feedback and support: TensorBlock's  <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a>
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## Weyaxi/Einstein-v7-Qwen2-7B - GGUF

This repo contains GGUF format model files for [Weyaxi/Einstein-v7-Qwen2-7B](https://huggingface.co/Weyaxi/Einstein-v7-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).


<div style="text-align: left; margin: 20px 0;">
    <a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
        Run them on the TensorBlock client using your local machine ↗
    </a>
</div>

## 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 |
| -------- | ---------- | --------- | ----------- |
| [Einstein-v7-Qwen2-7B-Q2_K.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-Qwen2-7B-Q2_K.gguf) | Q2_K | 2.809 GB | smallest, significant quality loss - not recommended for most purposes |
| [Einstein-v7-Qwen2-7B-Q3_K_S.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-Qwen2-7B-Q3_K_S.gguf) | Q3_K_S | 3.253 GB | very small, high quality loss |
| [Einstein-v7-Qwen2-7B-Q3_K_M.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-Qwen2-7B-Q3_K_M.gguf) | Q3_K_M | 3.547 GB | very small, high quality loss |
| [Einstein-v7-Qwen2-7B-Q3_K_L.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-Qwen2-7B-Q3_K_L.gguf) | Q3_K_L | 3.808 GB | small, substantial quality loss |
| [Einstein-v7-Qwen2-7B-Q4_0.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-Qwen2-7B-Q4_0.gguf) | Q4_0 | 4.127 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [Einstein-v7-Qwen2-7B-Q4_K_S.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-Qwen2-7B-Q4_K_S.gguf) | Q4_K_S | 4.152 GB | small, greater quality loss |
| [Einstein-v7-Qwen2-7B-Q4_K_M.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-Qwen2-7B-Q4_K_M.gguf) | Q4_K_M | 4.361 GB | medium, balanced quality - recommended |
| [Einstein-v7-Qwen2-7B-Q5_0.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-Qwen2-7B-Q5_0.gguf) | Q5_0 | 4.950 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [Einstein-v7-Qwen2-7B-Q5_K_S.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-Qwen2-7B-Q5_K_S.gguf) | Q5_K_S | 4.950 GB | large, low quality loss - recommended |
| [Einstein-v7-Qwen2-7B-Q5_K_M.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-Qwen2-7B-Q5_K_M.gguf) | Q5_K_M | 5.071 GB | large, very low quality loss - recommended |
| [Einstein-v7-Qwen2-7B-Q6_K.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-Qwen2-7B-Q6_K.gguf) | Q6_K | 5.825 GB | very large, extremely low quality loss |
| [Einstein-v7-Qwen2-7B-Q8_0.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-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/Einstein-v7-Qwen2-7B-GGUF --include "Einstein-v7-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/Einstein-v7-Qwen2-7B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```