Instructions to use TheBloke/Magicoder-S-DS-6.7B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TheBloke/Magicoder-S-DS-6.7B-GGUF with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="TheBloke/Magicoder-S-DS-6.7B-GGUF")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("TheBloke/Magicoder-S-DS-6.7B-GGUF", dtype="auto")

llama-cpp-python

How to use TheBloke/Magicoder-S-DS-6.7B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="TheBloke/Magicoder-S-DS-6.7B-GGUF",
	filename="magicoder-s-ds-6.7b.Q2_K.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use TheBloke/Magicoder-S-DS-6.7B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf TheBloke/Magicoder-S-DS-6.7B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf TheBloke/Magicoder-S-DS-6.7B-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf TheBloke/Magicoder-S-DS-6.7B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf TheBloke/Magicoder-S-DS-6.7B-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/Magicoder-S-DS-6.7B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf TheBloke/Magicoder-S-DS-6.7B-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/Magicoder-S-DS-6.7B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf TheBloke/Magicoder-S-DS-6.7B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/TheBloke/Magicoder-S-DS-6.7B-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use TheBloke/Magicoder-S-DS-6.7B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TheBloke/Magicoder-S-DS-6.7B-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/Magicoder-S-DS-6.7B-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/TheBloke/Magicoder-S-DS-6.7B-GGUF:Q4_K_M

SGLang

How to use TheBloke/Magicoder-S-DS-6.7B-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/Magicoder-S-DS-6.7B-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/Magicoder-S-DS-6.7B-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/Magicoder-S-DS-6.7B-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/Magicoder-S-DS-6.7B-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Ollama
How to use TheBloke/Magicoder-S-DS-6.7B-GGUF with Ollama:
```
ollama run hf.co/TheBloke/Magicoder-S-DS-6.7B-GGUF:Q4_K_M
```

Unsloth Studio new

How to use TheBloke/Magicoder-S-DS-6.7B-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/Magicoder-S-DS-6.7B-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/Magicoder-S-DS-6.7B-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/Magicoder-S-DS-6.7B-GGUF to start chatting

Docker Model Runner
How to use TheBloke/Magicoder-S-DS-6.7B-GGUF with Docker Model Runner:
```
docker model run hf.co/TheBloke/Magicoder-S-DS-6.7B-GGUF:Q4_K_M
```

Lemonade

How to use TheBloke/Magicoder-S-DS-6.7B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull TheBloke/Magicoder-S-DS-6.7B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Magicoder-S-DS-6.7B-GGUF-Q4_K_M

List all available models

lemonade list

Couldn't load any GGUF file of the Magicoder S DS into oogabooga

by OrelMac - opened Dec 10, 2023

Discussion

OrelMac

Dec 10, 2023

Title.

When trying to load using cpp the following err msg appears :

Traceback (most recent call last):
File "D:\text-generation-webui-main\modules\ui_model_menu.py", line 209, in load_model_wrapper
shared.model, shared.tokenizer = load_model(shared.model_name, loader)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\text-generation-webui-main\modules\models.py", line 88, in load_model
output = load_func_maploader
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\text-generation-webui-main\modules\models.py", line 253, in llamacpp_loader
model, tokenizer = LlamaCppModel.from_pretrained(model_file)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\text-generation-webui-main\modules\llamacpp_model.py", line 91, in from_pretrained
result.model = Llama(**params)
^^^^^^^^^^^^^^^
File "D:\text-generation-webui-main\installer_files\env\Lib\site-packages\llama_cpp\llama.py", line 923, in init
self._n_vocab = self.n_vocab()
^^^^^^^^^^^^^^
File "D:\text-generation-webui-main\installer_files\env\Lib\site-packages\llama_cpp\llama.py", line 2184, in n_vocab
return self._model.n_vocab()
^^^^^^^^^^^^^^^^^^^^^
File "D:\text-generation-webui-main\installer_files\env\Lib\site-packages\llama_cpp\llama.py", line 250, in n_vocab
assert self.model is not None
^^^^^^^^^^^^^^^^^^^^^^
AssertionError

Exception ignored in: <function LlamaCppModel.__del__ at 0x0000024AD12E2E80>
Traceback (most recent call last):
File "D:\text-generation-webui-main\modules\llamacpp_model.py", line 49, in del
del self.model

samson14

Dec 15, 2023

Same issue.
Unable to use any gguf files.

shtirlic

Dec 29, 2023

The issue is still persist for this model on latest text-generation-webui

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