---
library_name: transformers
license: apache-2.0
datasets:
- databricks/databricks-dolly-15k
- glaiveai/glaive-code-assistant-v3
- glaiveai/glaive-function-calling-v2
- gretelai/synthetic_text_to_sql
- meta-math/MetaMathQA
- microsoft/orca-math-word-problems-200k
- neural-bridge/rag-dataset-12000
- neural-bridge/rag-hallucination-dataset-1000
- nvidia/HelpSteer
- OpenAssistant/oasst2
language:
- en
- ja
tags:
- mixtral
- steerlm
- TensorBlock
- GGUF
base_model: karakuri-ai/karakuri-lm-8x7b-instruct-v0.1
---

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</div>
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        <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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## karakuri-ai/karakuri-lm-8x7b-instruct-v0.1 - GGUF

This repo contains GGUF format model files for [karakuri-ai/karakuri-lm-8x7b-instruct-v0.1](https://huggingface.co/karakuri-ai/karakuri-lm-8x7b-instruct-v0.1).

The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4242](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

```
<s><|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>{system_prompt}<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|USER_TOKEN|>{prompt}<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|><attributes>helpfulness: 4 correctness: 4 coherence: 4 complexity: 4 verbosity: 4 quality: 4 toxicity: 0 humor: 0 creativity: 0</attributes>
```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [karakuri-lm-8x7b-instruct-v0.1-Q2_K.gguf](https://huggingface.co/tensorblock/karakuri-lm-8x7b-instruct-v0.1-GGUF/blob/main/karakuri-lm-8x7b-instruct-v0.1-Q2_K.gguf) | Q2_K | 17.312 GB | smallest, significant quality loss - not recommended for most purposes |
| [karakuri-lm-8x7b-instruct-v0.1-Q3_K_S.gguf](https://huggingface.co/tensorblock/karakuri-lm-8x7b-instruct-v0.1-GGUF/blob/main/karakuri-lm-8x7b-instruct-v0.1-Q3_K_S.gguf) | Q3_K_S | 20.433 GB | very small, high quality loss |
| [karakuri-lm-8x7b-instruct-v0.1-Q3_K_M.gguf](https://huggingface.co/tensorblock/karakuri-lm-8x7b-instruct-v0.1-GGUF/blob/main/karakuri-lm-8x7b-instruct-v0.1-Q3_K_M.gguf) | Q3_K_M | 22.547 GB | very small, high quality loss |
| [karakuri-lm-8x7b-instruct-v0.1-Q3_K_L.gguf](https://huggingface.co/tensorblock/karakuri-lm-8x7b-instruct-v0.1-GGUF/blob/main/karakuri-lm-8x7b-instruct-v0.1-Q3_K_L.gguf) | Q3_K_L | 24.170 GB | small, substantial quality loss |
| [karakuri-lm-8x7b-instruct-v0.1-Q4_0.gguf](https://huggingface.co/tensorblock/karakuri-lm-8x7b-instruct-v0.1-GGUF/blob/main/karakuri-lm-8x7b-instruct-v0.1-Q4_0.gguf) | Q4_0 | 26.444 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [karakuri-lm-8x7b-instruct-v0.1-Q4_K_S.gguf](https://huggingface.co/tensorblock/karakuri-lm-8x7b-instruct-v0.1-GGUF/blob/main/karakuri-lm-8x7b-instruct-v0.1-Q4_K_S.gguf) | Q4_K_S | 26.746 GB | small, greater quality loss |
| [karakuri-lm-8x7b-instruct-v0.1-Q4_K_M.gguf](https://huggingface.co/tensorblock/karakuri-lm-8x7b-instruct-v0.1-GGUF/blob/main/karakuri-lm-8x7b-instruct-v0.1-Q4_K_M.gguf) | Q4_K_M | 28.449 GB | medium, balanced quality - recommended |
| [karakuri-lm-8x7b-instruct-v0.1-Q5_0.gguf](https://huggingface.co/tensorblock/karakuri-lm-8x7b-instruct-v0.1-GGUF/blob/main/karakuri-lm-8x7b-instruct-v0.1-Q5_0.gguf) | Q5_0 | 32.232 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [karakuri-lm-8x7b-instruct-v0.1-Q5_K_S.gguf](https://huggingface.co/tensorblock/karakuri-lm-8x7b-instruct-v0.1-GGUF/blob/main/karakuri-lm-8x7b-instruct-v0.1-Q5_K_S.gguf) | Q5_K_S | 32.232 GB | large, low quality loss - recommended |
| [karakuri-lm-8x7b-instruct-v0.1-Q5_K_M.gguf](https://huggingface.co/tensorblock/karakuri-lm-8x7b-instruct-v0.1-GGUF/blob/main/karakuri-lm-8x7b-instruct-v0.1-Q5_K_M.gguf) | Q5_K_M | 33.230 GB | large, very low quality loss - recommended |
| [karakuri-lm-8x7b-instruct-v0.1-Q6_K.gguf](https://huggingface.co/tensorblock/karakuri-lm-8x7b-instruct-v0.1-GGUF/blob/main/karakuri-lm-8x7b-instruct-v0.1-Q6_K.gguf) | Q6_K | 38.382 GB | very large, extremely low quality loss |
| [karakuri-lm-8x7b-instruct-v0.1-Q8_0.gguf](https://huggingface.co/tensorblock/karakuri-lm-8x7b-instruct-v0.1-GGUF/blob/main/karakuri-lm-8x7b-instruct-v0.1-Q8_0.gguf) | Q8_0 | 49.627 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/karakuri-lm-8x7b-instruct-v0.1-GGUF --include "karakuri-lm-8x7b-instruct-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:

```shell
huggingface-cli download tensorblock/karakuri-lm-8x7b-instruct-v0.1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```