---
license: apache-2.0
tags:
- LLMs
- mistral
- Intel
- TensorBlock
- GGUF
pipeline_tag: text-generation
base_model: Intel/neural-chat-7b-v3-1
datasets:
- Open-Orca/SlimOrca
language:
- en
model-index:
- name: neural-chat-7b-v3-1
  results:
  - task:
      type: Large Language Model
      name: Large Language Model
    dataset:
      name: Open-Orca/SlimOrca
      type: Open-Orca/SlimOrca
    metrics:
    - type: ARC (25-shot)
      value: 66.21
      name: ARC (25-shot)
      verified: true
    - type: HellaSwag (10-shot)
      value: 83.64
      name: HellaSwag (10-shot)
      verified: true
    - type: MMLU (5-shot)
      value: 62.37
      name: MMLU (5-shot)
      verified: true
    - type: TruthfulQA (0-shot)
      value: 59.65
      name: TruthfulQA (0-shot)
      verified: true
    - type: Winogrande (5-shot)
      value: 78.14
      name: Winogrande (5-shot)
      verified: true
    - type: GSM8K (5-shot)
      value: 19.56
      name: GSM8K (5-shot)
      verified: true
    - type: DROP (3-shot)
      value: 43.84
      name: DROP (3-shot)
      verified: true
---

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## Intel/neural-chat-7b-v3-1 - GGUF

This repo contains GGUF format model files for [Intel/neural-chat-7b-v3-1](https://huggingface.co/Intel/neural-chat-7b-v3-1).

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


```
### System:
{system_prompt}
### User:
{prompt} 
### Assistant:
```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [neural-chat-7b-v3-1-Q2_K.gguf](https://huggingface.co/tensorblock/neural-chat-7b-v3-1-GGUF/blob/main/neural-chat-7b-v3-1-Q2_K.gguf) | Q2_K | 2.532 GB | smallest, significant quality loss - not recommended for most purposes |
| [neural-chat-7b-v3-1-Q3_K_S.gguf](https://huggingface.co/tensorblock/neural-chat-7b-v3-1-GGUF/blob/main/neural-chat-7b-v3-1-Q3_K_S.gguf) | Q3_K_S | 2.947 GB | very small, high quality loss |
| [neural-chat-7b-v3-1-Q3_K_M.gguf](https://huggingface.co/tensorblock/neural-chat-7b-v3-1-GGUF/blob/main/neural-chat-7b-v3-1-Q3_K_M.gguf) | Q3_K_M | 3.277 GB | very small, high quality loss |
| [neural-chat-7b-v3-1-Q3_K_L.gguf](https://huggingface.co/tensorblock/neural-chat-7b-v3-1-GGUF/blob/main/neural-chat-7b-v3-1-Q3_K_L.gguf) | Q3_K_L | 3.560 GB | small, substantial quality loss |
| [neural-chat-7b-v3-1-Q4_0.gguf](https://huggingface.co/tensorblock/neural-chat-7b-v3-1-GGUF/blob/main/neural-chat-7b-v3-1-Q4_0.gguf) | Q4_0 | 3.827 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [neural-chat-7b-v3-1-Q4_K_S.gguf](https://huggingface.co/tensorblock/neural-chat-7b-v3-1-GGUF/blob/main/neural-chat-7b-v3-1-Q4_K_S.gguf) | Q4_K_S | 3.856 GB | small, greater quality loss |
| [neural-chat-7b-v3-1-Q4_K_M.gguf](https://huggingface.co/tensorblock/neural-chat-7b-v3-1-GGUF/blob/main/neural-chat-7b-v3-1-Q4_K_M.gguf) | Q4_K_M | 4.068 GB | medium, balanced quality - recommended |
| [neural-chat-7b-v3-1-Q5_0.gguf](https://huggingface.co/tensorblock/neural-chat-7b-v3-1-GGUF/blob/main/neural-chat-7b-v3-1-Q5_0.gguf) | Q5_0 | 4.654 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [neural-chat-7b-v3-1-Q5_K_S.gguf](https://huggingface.co/tensorblock/neural-chat-7b-v3-1-GGUF/blob/main/neural-chat-7b-v3-1-Q5_K_S.gguf) | Q5_K_S | 4.654 GB | large, low quality loss - recommended |
| [neural-chat-7b-v3-1-Q5_K_M.gguf](https://huggingface.co/tensorblock/neural-chat-7b-v3-1-GGUF/blob/main/neural-chat-7b-v3-1-Q5_K_M.gguf) | Q5_K_M | 4.779 GB | large, very low quality loss - recommended |
| [neural-chat-7b-v3-1-Q6_K.gguf](https://huggingface.co/tensorblock/neural-chat-7b-v3-1-GGUF/blob/main/neural-chat-7b-v3-1-Q6_K.gguf) | Q6_K | 5.534 GB | very large, extremely low quality loss |
| [neural-chat-7b-v3-1-Q8_0.gguf](https://huggingface.co/tensorblock/neural-chat-7b-v3-1-GGUF/blob/main/neural-chat-7b-v3-1-Q8_0.gguf) | Q8_0 | 7.167 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/neural-chat-7b-v3-1-GGUF --include "neural-chat-7b-v3-1-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/neural-chat-7b-v3-1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```