Instructions to use second-state/Deepseek-Coder-6.7B-Instruct-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use second-state/Deepseek-Coder-6.7B-Instruct-GGUF with Transformers:

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

pipe = pipeline("text-generation", model="second-state/Deepseek-Coder-6.7B-Instruct-GGUF")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("second-state/Deepseek-Coder-6.7B-Instruct-GGUF")
model = AutoModelForCausalLM.from_pretrained("second-state/Deepseek-Coder-6.7B-Instruct-GGUF")

llama-cpp-python

How to use second-state/Deepseek-Coder-6.7B-Instruct-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="second-state/Deepseek-Coder-6.7B-Instruct-GGUF",
	filename="deepseek-coder-6.7b-instruct-Q2_K.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use second-state/Deepseek-Coder-6.7B-Instruct-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf second-state/Deepseek-Coder-6.7B-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf second-state/Deepseek-Coder-6.7B-Instruct-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 second-state/Deepseek-Coder-6.7B-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf second-state/Deepseek-Coder-6.7B-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 second-state/Deepseek-Coder-6.7B-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf second-state/Deepseek-Coder-6.7B-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 second-state/Deepseek-Coder-6.7B-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf second-state/Deepseek-Coder-6.7B-Instruct-GGUF:Q4_K_M

Use Docker

docker model run hf.co/second-state/Deepseek-Coder-6.7B-Instruct-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use second-state/Deepseek-Coder-6.7B-Instruct-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "second-state/Deepseek-Coder-6.7B-Instruct-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "second-state/Deepseek-Coder-6.7B-Instruct-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/second-state/Deepseek-Coder-6.7B-Instruct-GGUF:Q4_K_M

SGLang

How to use second-state/Deepseek-Coder-6.7B-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 "second-state/Deepseek-Coder-6.7B-Instruct-GGUF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "second-state/Deepseek-Coder-6.7B-Instruct-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "second-state/Deepseek-Coder-6.7B-Instruct-GGUF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "second-state/Deepseek-Coder-6.7B-Instruct-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use second-state/Deepseek-Coder-6.7B-Instruct-GGUF with Ollama:
```
ollama run hf.co/second-state/Deepseek-Coder-6.7B-Instruct-GGUF:Q4_K_M
```

Unsloth Studio

How to use second-state/Deepseek-Coder-6.7B-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 second-state/Deepseek-Coder-6.7B-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 second-state/Deepseek-Coder-6.7B-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 second-state/Deepseek-Coder-6.7B-Instruct-GGUF to start chatting

Docker Model Runner
How to use second-state/Deepseek-Coder-6.7B-Instruct-GGUF with Docker Model Runner:
```
docker model run hf.co/second-state/Deepseek-Coder-6.7B-Instruct-GGUF:Q4_K_M
```

Lemonade

How to use second-state/Deepseek-Coder-6.7B-Instruct-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull second-state/Deepseek-Coder-6.7B-Instruct-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Deepseek-Coder-6.7B-Instruct-GGUF-Q4_K_M

List all available models

lemonade list

second-state
/

Deepseek-Coder-6.7B-Instruct-GGUF

Add models

+version https://git-lfs.github.com/spec/v1
+oid sha256:342bfc01b7028fca291ab90e331127fab4cad78afdcbb5e1f9936a406d4841ad
+size 2534630336

+version https://git-lfs.github.com/spec/v1
+oid sha256:e874f82b7e38ccc2914fbd680149c8bde7c719d3c038abe750dfb48ad2fb0ddc
+size 3598984128

+version https://git-lfs.github.com/spec/v1
+oid sha256:83c29200bc472a881cc4d65a4aa7ba7dfd6284043e7b7b3eb4f9078d78b32339
+size 3299877824

+version https://git-lfs.github.com/spec/v1
+oid sha256:8119adb94c689fbfdc8e542ef39e73692f42af1a0ab01aa12c2bbae90ac3d868
+size 2950177728

+version https://git-lfs.github.com/spec/v1
+oid sha256:3f61183151ec77900b595c52075e26cb1e185f5140ccc2fa09d4f588f65a91bc
+size 3827819456

+version https://git-lfs.github.com/spec/v1
+oid sha256:786e1d90ef74d3555cfbc9bb8ea5352e308b757a152b9fbd4f1f4380a877af0a
+size 4083016640

+version https://git-lfs.github.com/spec/v1
+oid sha256:c3b78bc5ab63bc961508c849d68d45f45f0054120b67ce3faf417c6bb1dd3593
+size 3858752448

+version https://git-lfs.github.com/spec/v1
+oid sha256:d0b7729ec3f595b0ca7ba5e2ca4c56398c4d2d27feb035f147b471a26b88faa4
+size 4653835200

+version https://git-lfs.github.com/spec/v1
+oid sha256:81c6fb56729ca9f95a73edd23ad58b4e64a27b53d0171a03716690b4bed8b2fc
+size 4785300416

+version https://git-lfs.github.com/spec/v1
+oid sha256:6ce63db9906bcda9370f06006490c04662329dd958db6ebdda1f24b5ed0f32b0
+size 5531476928

	@@ -0,0 +1,3 @@

	@@ -0,0 +1,3 @@

	@@ -0,0 +1,3 @@

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:3740dc08d61a3483f4c29fcd48c254cc29697ac1c9eafd4f2ea9edca039c4ebc
+size 7163880384