Instructions to use rizkysulaeman/DeepSeek-R1-Distill-Llama-8B-FineTune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use rizkysulaeman/DeepSeek-R1-Distill-Llama-8B-FineTune with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="rizkysulaeman/DeepSeek-R1-Distill-Llama-8B-FineTune",
	filename="unsloth.F16.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use rizkysulaeman/DeepSeek-R1-Distill-Llama-8B-FineTune with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf rizkysulaeman/DeepSeek-R1-Distill-Llama-8B-FineTune:F16
# Run inference directly in the terminal:
llama-cli -hf rizkysulaeman/DeepSeek-R1-Distill-Llama-8B-FineTune:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf rizkysulaeman/DeepSeek-R1-Distill-Llama-8B-FineTune:F16
# Run inference directly in the terminal:
llama-cli -hf rizkysulaeman/DeepSeek-R1-Distill-Llama-8B-FineTune:F16

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 rizkysulaeman/DeepSeek-R1-Distill-Llama-8B-FineTune:F16
# Run inference directly in the terminal:
./llama-cli -hf rizkysulaeman/DeepSeek-R1-Distill-Llama-8B-FineTune:F16

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 rizkysulaeman/DeepSeek-R1-Distill-Llama-8B-FineTune:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf rizkysulaeman/DeepSeek-R1-Distill-Llama-8B-FineTune:F16

Use Docker

docker model run hf.co/rizkysulaeman/DeepSeek-R1-Distill-Llama-8B-FineTune:F16

LM Studio
Jan
Ollama
How to use rizkysulaeman/DeepSeek-R1-Distill-Llama-8B-FineTune with Ollama:
```
ollama run hf.co/rizkysulaeman/DeepSeek-R1-Distill-Llama-8B-FineTune:F16
```

Unsloth Studio

How to use rizkysulaeman/DeepSeek-R1-Distill-Llama-8B-FineTune 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 rizkysulaeman/DeepSeek-R1-Distill-Llama-8B-FineTune 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 rizkysulaeman/DeepSeek-R1-Distill-Llama-8B-FineTune to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for rizkysulaeman/DeepSeek-R1-Distill-Llama-8B-FineTune to start chatting

Docker Model Runner
How to use rizkysulaeman/DeepSeek-R1-Distill-Llama-8B-FineTune with Docker Model Runner:
```
docker model run hf.co/rizkysulaeman/DeepSeek-R1-Distill-Llama-8B-FineTune:F16
```

Lemonade

How to use rizkysulaeman/DeepSeek-R1-Distill-Llama-8B-FineTune with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull rizkysulaeman/DeepSeek-R1-Distill-Llama-8B-FineTune:F16

Run and chat with the model

lemonade run user.DeepSeek-R1-Distill-Llama-8B-FineTune-F16

List all available models

lemonade list

DeepSeek-R1 Release

⚡ Performance on par with OpenAI-o1

📖 Fully open-source model & technical report

🏆 MIT licensed: Distill & commercialize freely!

🌐 Website & API are live now! Try DeepThink at chat.deepseek.com today!

🔥 Bonus: Open-Source Distilled Models!

🔬 Distilled from DeepSeek-R1, 6 small models fully open-sourced

📏 32B & 70B models on par with OpenAI-o1-mini

🤝 Empowering the open-source community

🌍 Pushing the boundaries of open AI!

🛠️ DeepSeek-R1: Technical Highlights

📈 Large-scale RL in post-training

🏆 Significant performance boost with minimal labeled data

🔢 Math, code, and reasoning tasks on par with OpenAI-o1

📄 More details: https://github.com/deepseek-ai/DeepSeek-R1/blob/main/DeepSeek_R1.pdf

🌐 API Access & Pricing

⚙️ Use DeepSeek-R1 by setting model=deepseek-reasoner

💰 $0.14 / million input tokens (cache hit)

💰 $0.55 / million input tokens (cache miss)

💰 $2.19 / million output tokens

📖 API guide: https://api-docs.deepseek.com/guides/reasoning_model

Downloads last month: 35

GGUF

Model size

8B params

Architecture

llama

Hardware compatibility

16-bit

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