---
extra_gated_heading: Access Llama 2 on Hugging Face
extra_gated_description: This is a form to enable access to Llama 2 on Hugging Face
  after you have been granted access from Meta. Please visit the [Meta website](https://ai.meta.com/resources/models-and-libraries/llama-downloads)
  and accept our license terms and acceptable use policy before submitting this form.
  Requests will be processed in 1-2 days.
extra_gated_prompt: '**Your Hugging Face account email address MUST match the email
  you provide on the Meta website, or your request will not be approved.**'
extra_gated_button_content: Submit
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  ? I agree to share my name, email address and username with Meta and confirm that
    I have already been granted download access on the Meta website
  : checkbox
language:
- en
pipeline_tag: text-generation
inference: false
arxiv: 2307.09288
tags:
- facebook
- meta
- pytorch
- llama
- llama-2
- TensorBlock
- GGUF
base_model: TheBloke/Llama-2-7B-Chat-fp16
---

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## TheBloke/Llama-2-7B-Chat-fp16 - GGUF

This repo contains GGUF format model files for [TheBloke/Llama-2-7B-Chat-fp16](https://huggingface.co/TheBloke/Llama-2-7B-Chat-fp16).

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


```

```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [Llama-2-7B-Chat-fp16-Q2_K.gguf](https://huggingface.co/tensorblock/Llama-2-7B-Chat-fp16-GGUF/blob/main/Llama-2-7B-Chat-fp16-Q2_K.gguf) | Q2_K | 2.359 GB | smallest, significant quality loss - not recommended for most purposes |
| [Llama-2-7B-Chat-fp16-Q3_K_S.gguf](https://huggingface.co/tensorblock/Llama-2-7B-Chat-fp16-GGUF/blob/main/Llama-2-7B-Chat-fp16-Q3_K_S.gguf) | Q3_K_S | 2.746 GB | very small, high quality loss |
| [Llama-2-7B-Chat-fp16-Q3_K_M.gguf](https://huggingface.co/tensorblock/Llama-2-7B-Chat-fp16-GGUF/blob/main/Llama-2-7B-Chat-fp16-Q3_K_M.gguf) | Q3_K_M | 3.072 GB | very small, high quality loss |
| [Llama-2-7B-Chat-fp16-Q3_K_L.gguf](https://huggingface.co/tensorblock/Llama-2-7B-Chat-fp16-GGUF/blob/main/Llama-2-7B-Chat-fp16-Q3_K_L.gguf) | Q3_K_L | 3.350 GB | small, substantial quality loss |
| [Llama-2-7B-Chat-fp16-Q4_0.gguf](https://huggingface.co/tensorblock/Llama-2-7B-Chat-fp16-GGUF/blob/main/Llama-2-7B-Chat-fp16-Q4_0.gguf) | Q4_0 | 3.563 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [Llama-2-7B-Chat-fp16-Q4_K_S.gguf](https://huggingface.co/tensorblock/Llama-2-7B-Chat-fp16-GGUF/blob/main/Llama-2-7B-Chat-fp16-Q4_K_S.gguf) | Q4_K_S | 3.592 GB | small, greater quality loss |
| [Llama-2-7B-Chat-fp16-Q4_K_M.gguf](https://huggingface.co/tensorblock/Llama-2-7B-Chat-fp16-GGUF/blob/main/Llama-2-7B-Chat-fp16-Q4_K_M.gguf) | Q4_K_M | 3.801 GB | medium, balanced quality - recommended |
| [Llama-2-7B-Chat-fp16-Q5_0.gguf](https://huggingface.co/tensorblock/Llama-2-7B-Chat-fp16-GGUF/blob/main/Llama-2-7B-Chat-fp16-Q5_0.gguf) | Q5_0 | 4.332 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [Llama-2-7B-Chat-fp16-Q5_K_S.gguf](https://huggingface.co/tensorblock/Llama-2-7B-Chat-fp16-GGUF/blob/main/Llama-2-7B-Chat-fp16-Q5_K_S.gguf) | Q5_K_S | 4.332 GB | large, low quality loss - recommended |
| [Llama-2-7B-Chat-fp16-Q5_K_M.gguf](https://huggingface.co/tensorblock/Llama-2-7B-Chat-fp16-GGUF/blob/main/Llama-2-7B-Chat-fp16-Q5_K_M.gguf) | Q5_K_M | 4.455 GB | large, very low quality loss - recommended |
| [Llama-2-7B-Chat-fp16-Q6_K.gguf](https://huggingface.co/tensorblock/Llama-2-7B-Chat-fp16-GGUF/blob/main/Llama-2-7B-Chat-fp16-Q6_K.gguf) | Q6_K | 5.149 GB | very large, extremely low quality loss |
| [Llama-2-7B-Chat-fp16-Q8_0.gguf](https://huggingface.co/tensorblock/Llama-2-7B-Chat-fp16-GGUF/blob/main/Llama-2-7B-Chat-fp16-Q8_0.gguf) | Q8_0 | 6.669 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/Llama-2-7B-Chat-fp16-GGUF --include "Llama-2-7B-Chat-fp16-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/Llama-2-7B-Chat-fp16-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```