---
datasets:
- tiiuae/falcon-refinedweb
language:
- en
inference: true
widget:
- text: Hey Falcon! Any recommendations for my holidays in Abu Dhabi?
  example_title: Abu Dhabi Trip
- text: What's the Everett interpretation of quantum mechanics?
  example_title: 'Q/A: Quantum & Answers'
- text: Give me a list of the top 10 dive sites you would recommend around the world.
  example_title: Diving Top 10
- text: Can you tell me more about deep-water soloing?
  example_title: Extreme sports
- text: Can you write a short tweet about the Apache 2.0 release of our latest AI
    model, Falcon LLM?
  example_title: Twitter Helper
- text: What are the responsabilities of a Chief Llama Officer?
  example_title: Trendy Jobs
license: apache-2.0
base_model: vilsonrodrigues/falcon-7b-instruct-sharded
tags:
- TensorBlock
- GGUF
---

<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>
        </p>
    </div>
</div>

## vilsonrodrigues/falcon-7b-instruct-sharded - GGUF

This repo contains GGUF format model files for [vilsonrodrigues/falcon-7b-instruct-sharded](https://huggingface.co/vilsonrodrigues/falcon-7b-instruct-sharded).

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

```

```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [falcon-7b-instruct-sharded-Q2_K.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q2_K.gguf) | Q2_K | 3.440 GB | smallest, significant quality loss - not recommended for most purposes |
| [falcon-7b-instruct-sharded-Q3_K_S.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q3_K_S.gguf) | Q3_K_S | 3.440 GB | very small, high quality loss |
| [falcon-7b-instruct-sharded-Q3_K_M.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q3_K_M.gguf) | Q3_K_M | 3.702 GB | very small, high quality loss |
| [falcon-7b-instruct-sharded-Q3_K_L.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q3_K_L.gguf) | Q3_K_L | 3.923 GB | small, substantial quality loss |
| [falcon-7b-instruct-sharded-Q4_0.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q4_0.gguf) | Q4_0 | 3.767 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [falcon-7b-instruct-sharded-Q4_K_S.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q4_K_S.gguf) | Q4_K_S | 4.230 GB | small, greater quality loss |
| [falcon-7b-instruct-sharded-Q4_K_M.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q4_K_M.gguf) | Q4_K_M | 4.444 GB | medium, balanced quality - recommended |
| [falcon-7b-instruct-sharded-Q5_0.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q5_0.gguf) | Q5_0 | 4.538 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [falcon-7b-instruct-sharded-Q5_K_S.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q5_K_S.gguf) | Q5_K_S | 4.770 GB | large, low quality loss - recommended |
| [falcon-7b-instruct-sharded-Q5_K_M.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q5_K_M.gguf) | Q5_K_M | 5.131 GB | large, very low quality loss - recommended |
| [falcon-7b-instruct-sharded-Q6_K.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q6_K.gguf) | Q6_K | 6.256 GB | very large, extremely low quality loss |
| [falcon-7b-instruct-sharded-Q8_0.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q8_0.gguf) | Q8_0 | 6.852 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/falcon-7b-instruct-sharded-GGUF --include "falcon-7b-instruct-sharded-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/falcon-7b-instruct-sharded-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```