Instructions to use TheBloke/CodeLlama-13B-Instruct-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheBloke/CodeLlama-13B-Instruct-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TheBloke/CodeLlama-13B-Instruct-GGUF")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TheBloke/CodeLlama-13B-Instruct-GGUF", dtype="auto") - llama-cpp-python
How to use TheBloke/CodeLlama-13B-Instruct-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="TheBloke/CodeLlama-13B-Instruct-GGUF", filename="codellama-13b-instruct.Q2_K.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use TheBloke/CodeLlama-13B-Instruct-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf TheBloke/CodeLlama-13B-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf TheBloke/CodeLlama-13B-Instruct-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf TheBloke/CodeLlama-13B-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf TheBloke/CodeLlama-13B-Instruct-GGUF:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf TheBloke/CodeLlama-13B-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf TheBloke/CodeLlama-13B-Instruct-GGUF:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf TheBloke/CodeLlama-13B-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf TheBloke/CodeLlama-13B-Instruct-GGUF:Q4_K_M
Use Docker
docker model run hf.co/TheBloke/CodeLlama-13B-Instruct-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use TheBloke/CodeLlama-13B-Instruct-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TheBloke/CodeLlama-13B-Instruct-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TheBloke/CodeLlama-13B-Instruct-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/TheBloke/CodeLlama-13B-Instruct-GGUF:Q4_K_M
- SGLang
How to use TheBloke/CodeLlama-13B-Instruct-GGUF with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "TheBloke/CodeLlama-13B-Instruct-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TheBloke/CodeLlama-13B-Instruct-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "TheBloke/CodeLlama-13B-Instruct-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TheBloke/CodeLlama-13B-Instruct-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Ollama
How to use TheBloke/CodeLlama-13B-Instruct-GGUF with Ollama:
ollama run hf.co/TheBloke/CodeLlama-13B-Instruct-GGUF:Q4_K_M
- Unsloth Studio
How to use TheBloke/CodeLlama-13B-Instruct-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for TheBloke/CodeLlama-13B-Instruct-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for TheBloke/CodeLlama-13B-Instruct-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for TheBloke/CodeLlama-13B-Instruct-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use TheBloke/CodeLlama-13B-Instruct-GGUF with Docker Model Runner:
docker model run hf.co/TheBloke/CodeLlama-13B-Instruct-GGUF:Q4_K_M
- Lemonade
How to use TheBloke/CodeLlama-13B-Instruct-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull TheBloke/CodeLlama-13B-Instruct-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.CodeLlama-13B-Instruct-GGUF-Q4_K_M
List all available models
lemonade list
Phatom Talking
When I try loading any (7, 13,34) of your GGUF models (regardless of instruct or text completion) in interactive mode, it starts generating random code like below. I am running this with a vanilla command -m codellama-13b-instruct.Q8_0.gguf --color -i. Has anyone else seen this?
== Running in interactive mode. ==
- Press Ctrl+C to interject at any time.
- Press Return to return control to LLaMa.
- To return control without starting a new line, end your input with '/'.
- If you want to submit another line, end your input with '\'.
using System;
using System.Collections.Generic;
using System.Lin
Yes, similar behavior here for codellama-13b-instruct.Q5_K_S.gguf and a variety of settings. For instance, for
./main -t 8 -ngl 32 -m models/13B/codellama-13b-instruct.Q5_K_S.gguf --color -c 8192 --temp 0.3 --rope-freq-base 10000 --rope-freq-scale 0.5 -i
I get:
== Running in interactive mode. ==
Press Ctrl+C to interject at any time.
Press Return to return control to LLaMa.
To return control without starting a new line, end your input with '/'.
If you want to submit another line, end your input with ''.
if ( ! isset( $settings['icon'] ) || empty( $settings['icon'] ) ) { $settings['icon'] = 'fa fa-star'; } if ( ! isset( $settings['color'] ) || empty( $settings['color'] ) ) { $settings['color'] = '#f1d204'; } if ( ! isset( $settings['size'] ) || empty( $settings['size'] ) ) { $settings['size'] = '35px'; } if ( ! isset( $settings['margin_top'] ) || empty( $settings['margin_top'] ) ) {
For the prompt method, using -f codellama.prompt with
codellama.prompt content:
[INST]
<>
You are a helpful, respectful and honest assistant.
If you are unsure about an answer, truthfully say 'I don't know'.
<>
Write a story about llamas
[/INST]
I get a reasonable output:
Once upon a time, in the Andes mountains of South America, there lived a group of llamas. These llamas were known for their soft, woolly coats and their gentle nature. They spent their days grazing on the lush grasses of the Andes, and at night they would gather together to rest and sleep.
One day, a young llama named Luna decided that she wanted to explore the world beyond her home in the Andes. She packed a small bag with some food and water, and set off on her journey.
Luna traveled for many days, through mountains and valleys, until she finally reached a new land. This land was filled with strange creatures and plants that Luna had never seen before. But despite the challenges of this new world, Luna was determined to make it her home.
And so, Luna settled down in her new land, surrounded by the strange and wondrous creatures that she had encountered on her journey. She lived a long and happy life, and her story was passed down from generation to generation as a reminder of the power of determination and perseverance. [end of text]
Don't use --rope-freq-base with this model - the correct value is already included in the GGUF, and it is not 10000 for CodeLlama models
This will be affecting the quality of the output
I'll remove mention of that from CodeLlama GGUF READMEs
This still happens without that flag though. I tried this on a MBP and another computer with a nvidia GPU with the same thing happening. Is there a specific command I am suppose to use with main?
Just out of curiosity, what client backend were you guys using to load the model when the phantom talking happened? I'm not familiar with all of them that can load GGUF models. I don't recognize it from the text @deetungsten and @md2 has shared in this thread. Does this happen across different Client loading backends?