README.md

---
base_model: tiiuae/falcon-7b-instruct
datasets:
- tiiuae/falcon-refinedweb
language:
- en
license: apache-2.0
tags:
- llama-cpp
- gguf-my-repo
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
---

# Triangle104/falcon-7b-instruct-Q4_0-GGUF
This model was converted to GGUF format from [`tiiuae/falcon-7b-instruct`](https://huggingface.co/tiiuae/falcon-7b-instruct) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/tiiuae/falcon-7b-instruct) for more details on the model.

## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)

```bash
brew install llama.cpp

```
Invoke the llama.cpp server or the CLI.

### CLI:
```bash
llama-cli --hf-repo Triangle104/falcon-7b-instruct-Q4_0-GGUF --hf-file falcon-7b-instruct-q4_0.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Triangle104/falcon-7b-instruct-Q4_0-GGUF --hf-file falcon-7b-instruct-q4_0.gguf -c 2048
```

Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.
```
git clone https://github.com/ggerganov/llama.cpp
```

Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
```
cd llama.cpp && LLAMA_CURL=1 make
```

Step 3: Run inference through the main binary.
```
./llama-cli --hf-repo Triangle104/falcon-7b-instruct-Q4_0-GGUF --hf-file falcon-7b-instruct-q4_0.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Triangle104/falcon-7b-instruct-Q4_0-GGUF --hf-file falcon-7b-instruct-q4_0.gguf -c 2048
```