metadata
datasets:
- tiiuae/falcon-refinedweb
language:
- en
inference: true
new_version: tiiuae/falcon-11B
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: tiiuae/falcon-7b-instruct
tags:
- TensorBlock
- GGUF
tiiuae/falcon-7b-instruct - GGUF
This repo contains GGUF format model files for tiiuae/falcon-7b-instruct.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.
Our projects
| Forge | |
|---|---|
|
|
| An OpenAI-compatible multi-provider routing layer. | |
| 🚀 Try it now! 🚀 | |
| Awesome MCP Servers | TensorBlock Studio |
 |
 |
| A comprehensive collection of Model Context Protocol (MCP) servers. | A lightweight, open, and extensible multi-LLM interaction studio. |
| 👀 See what we built 👀 | 👀 See what we built 👀 |
{system_prompt}
User: {prompt}
Assistant:
Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| falcon-7b-instruct-Q2_K.gguf | Q2_K | 3.595 GB | smallest, significant quality loss - not recommended for most purposes |
| falcon-7b-instruct-Q3_K_S.gguf | Q3_K_S | 3.595 GB | very small, high quality loss |
| falcon-7b-instruct-Q3_K_M.gguf | Q3_K_M | 3.856 GB | very small, high quality loss |
| falcon-7b-instruct-Q3_K_L.gguf | Q3_K_L | 4.078 GB | small, substantial quality loss |
| falcon-7b-instruct-Q4_0.gguf | Q4_0 | 3.922 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| falcon-7b-instruct-Q4_K_S.gguf | Q4_K_S | 4.420 GB | small, greater quality loss |
| falcon-7b-instruct-Q4_K_M.gguf | Q4_K_M | 4.633 GB | medium, balanced quality - recommended |
| falcon-7b-instruct-Q5_0.gguf | Q5_0 | 4.727 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| falcon-7b-instruct-Q5_K_S.gguf | Q5_K_S | 4.976 GB | large, low quality loss - recommended |
| falcon-7b-instruct-Q5_K_M.gguf | Q5_K_M | 5.338 GB | large, very low quality loss - recommended |
| falcon-7b-instruct-Q6_K.gguf | Q6_K | 6.548 GB | very large, extremely low quality loss |
| falcon-7b-instruct-Q8_0.gguf | Q8_0 | 7.145 GB | very large, extremely low quality loss - not recommended |
Downloading instruction
Command line
Firstly, install Huggingface Client
pip install -U "huggingface_hub[cli]"
Then, downoad the individual model file the a local directory
huggingface-cli download tensorblock/falcon-7b-instruct-GGUF --include "falcon-7b-instruct-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:
huggingface-cli download tensorblock/falcon-7b-instruct-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'