metadata
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
Kondara/falcon-7b-instruct-Q4_K_M-GGUF
This model was converted to GGUF format from tiiuae/falcon-7b-instruct
using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama-cli --hf-repo Kondara/falcon-7b-instruct-Q4_K_M-GGUF --hf-file falcon-7b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo Kondara/falcon-7b-instruct-Q4_K_M-GGUF --hf-file falcon-7b-instruct-q4_k_m.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps 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 Kondara/falcon-7b-instruct-Q4_K_M-GGUF --hf-file falcon-7b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo Kondara/falcon-7b-instruct-Q4_K_M-GGUF --hf-file falcon-7b-instruct-q4_k_m.gguf -c 2048