Instructions to use Kaleemullah/DeepSeek-R1-Distill-Llama-8B-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Kaleemullah/DeepSeek-R1-Distill-Llama-8B-gguf with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Kaleemullah/DeepSeek-R1-Distill-Llama-8B-gguf", filename="deepseek-ai-deepseek-r1-distill-llama-8b-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 Kaleemullah/DeepSeek-R1-Distill-Llama-8B-gguf with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Kaleemullah/DeepSeek-R1-Distill-Llama-8B-gguf:F16 # Run inference directly in the terminal: llama-cli -hf Kaleemullah/DeepSeek-R1-Distill-Llama-8B-gguf:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Kaleemullah/DeepSeek-R1-Distill-Llama-8B-gguf:F16 # Run inference directly in the terminal: llama-cli -hf Kaleemullah/DeepSeek-R1-Distill-Llama-8B-gguf: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 Kaleemullah/DeepSeek-R1-Distill-Llama-8B-gguf:F16 # Run inference directly in the terminal: ./llama-cli -hf Kaleemullah/DeepSeek-R1-Distill-Llama-8B-gguf: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 Kaleemullah/DeepSeek-R1-Distill-Llama-8B-gguf:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Kaleemullah/DeepSeek-R1-Distill-Llama-8B-gguf:F16
Use Docker
docker model run hf.co/Kaleemullah/DeepSeek-R1-Distill-Llama-8B-gguf:F16
- LM Studio
- Jan
- Ollama
How to use Kaleemullah/DeepSeek-R1-Distill-Llama-8B-gguf with Ollama:
ollama run hf.co/Kaleemullah/DeepSeek-R1-Distill-Llama-8B-gguf:F16
- Unsloth Studio
How to use Kaleemullah/DeepSeek-R1-Distill-Llama-8B-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 Kaleemullah/DeepSeek-R1-Distill-Llama-8B-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 Kaleemullah/DeepSeek-R1-Distill-Llama-8B-gguf to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Kaleemullah/DeepSeek-R1-Distill-Llama-8B-gguf to start chatting
- Docker Model Runner
How to use Kaleemullah/DeepSeek-R1-Distill-Llama-8B-gguf with Docker Model Runner:
docker model run hf.co/Kaleemullah/DeepSeek-R1-Distill-Llama-8B-gguf:F16
- Lemonade
How to use Kaleemullah/DeepSeek-R1-Distill-Llama-8B-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Kaleemullah/DeepSeek-R1-Distill-Llama-8B-gguf:F16
Run and chat with the model
lemonade run user.DeepSeek-R1-Distill-Llama-8B-gguf-F16
List all available models
lemonade list
deepseek-ai-deepseek-r1-distill-llama-8b-f16
This repository contains GGUF quantized models converted from deepseek-ai/DeepSeek-R1-Distill-Llama-8B.
Model Details
- Original Model: deepseek-ai/DeepSeek-R1-Distill-Llama-8B
- Quantization: F16
- File Size: ~14.97 GB
- Format: GGUF (llama.cpp compatible)
- Converted by: Kaleemullah
Quantization Information
- F16: Half precision (16-bit floating point)
Usage
With llama.cpp
# Download the model
huggingface-cli download Kaleemullah/deepseek-ai-deepseek-r1-distill-llama-8b-f16 deepseek-ai-deepseek-r1-distill-llama-8b-f16.gguf --local-dir ./models
# Run inference
./llama-cli -m ./models/deepseek-ai-deepseek-r1-distill-llama-8b-f16.gguf -p "Your prompt here"
With Python (llama-cpp-python)
from llama_cpp import Llama
# Load the model
llm = Llama(
model_path="./models/deepseek-ai-deepseek-r1-distill-llama-8b-f16.gguf",
n_ctx=2048, # Context window
n_gpu_layers=-1 # Use GPU if available
)
# Generate text
output = llm("Your prompt here", max_tokens=100)
print(output['choices'][0]['text'])
With Ollama
# Create a Modelfile
echo 'FROM ./models/deepseek-ai-deepseek-r1-distill-llama-8b-f16.gguf' > Modelfile
# Create the model
ollama create my-model -f Modelfile
# Run the model
ollama run my-model
Model Architecture
This is a quantized version of deepseek-ai/DeepSeek-R1-Distill-Llama-8B, optimized for efficient inference while maintaining model quality.
License
This model inherits the license from the original model: deepseek-ai/DeepSeek-R1-Distill-Llama-8B
Citation
If you use this model, please cite the original model:
@misc{deepseek-ai-DeepSeek-R1-Distill-Llama-8B,
author = {Original Model Authors},
title = {deepseek-ai/DeepSeek-R1-Distill-Llama-8B},
year = {2024},
publisher = {HuggingFace},
url = {https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Llama-8B}
}
Converted with
This model was converted using llama.cpp's convert_hf_to_gguf.py script.
Note: GGUF models are compatible with llama.cpp, Ollama, LM Studio, and other GGUF-compatible inference engines.
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deepseek-ai/DeepSeek-R1-Distill-Llama-8B