Instructions to use ReallyFloppyPenguin/DeepSeek-R1-Distill-Qwen-1.5B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use ReallyFloppyPenguin/DeepSeek-R1-Distill-Qwen-1.5B-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="ReallyFloppyPenguin/DeepSeek-R1-Distill-Qwen-1.5B-GGUF", filename="model-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 ReallyFloppyPenguin/DeepSeek-R1-Distill-Qwen-1.5B-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 ReallyFloppyPenguin/DeepSeek-R1-Distill-Qwen-1.5B-GGUF:F16 # Run inference directly in the terminal: llama cli -hf ReallyFloppyPenguin/DeepSeek-R1-Distill-Qwen-1.5B-GGUF:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf ReallyFloppyPenguin/DeepSeek-R1-Distill-Qwen-1.5B-GGUF:F16 # Run inference directly in the terminal: llama cli -hf ReallyFloppyPenguin/DeepSeek-R1-Distill-Qwen-1.5B-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 ReallyFloppyPenguin/DeepSeek-R1-Distill-Qwen-1.5B-GGUF:F16 # Run inference directly in the terminal: ./llama-cli -hf ReallyFloppyPenguin/DeepSeek-R1-Distill-Qwen-1.5B-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 ReallyFloppyPenguin/DeepSeek-R1-Distill-Qwen-1.5B-GGUF:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf ReallyFloppyPenguin/DeepSeek-R1-Distill-Qwen-1.5B-GGUF:F16
Use Docker
docker model run hf.co/ReallyFloppyPenguin/DeepSeek-R1-Distill-Qwen-1.5B-GGUF:F16
- LM Studio
- Jan
- Ollama
How to use ReallyFloppyPenguin/DeepSeek-R1-Distill-Qwen-1.5B-GGUF with Ollama:
ollama run hf.co/ReallyFloppyPenguin/DeepSeek-R1-Distill-Qwen-1.5B-GGUF:F16
- Unsloth Studio
How to use ReallyFloppyPenguin/DeepSeek-R1-Distill-Qwen-1.5B-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 ReallyFloppyPenguin/DeepSeek-R1-Distill-Qwen-1.5B-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 ReallyFloppyPenguin/DeepSeek-R1-Distill-Qwen-1.5B-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for ReallyFloppyPenguin/DeepSeek-R1-Distill-Qwen-1.5B-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use ReallyFloppyPenguin/DeepSeek-R1-Distill-Qwen-1.5B-GGUF with Docker Model Runner:
docker model run hf.co/ReallyFloppyPenguin/DeepSeek-R1-Distill-Qwen-1.5B-GGUF:F16
- Lemonade
How to use ReallyFloppyPenguin/DeepSeek-R1-Distill-Qwen-1.5B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ReallyFloppyPenguin/DeepSeek-R1-Distill-Qwen-1.5B-GGUF:F16
Run and chat with the model
lemonade run user.DeepSeek-R1-Distill-Qwen-1.5B-GGUF-F16
List all available models
lemonade list
| language: | |
| - en | |
| library_name: gguf | |
| base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B | |
| tags: | |
| - gguf | |
| - quantized | |
| - llama.cpp | |
| license: apache-2.0 | |
| # deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B - GGUF | |
| This repository contains GGUF quantizations of [deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B). | |
| ## About GGUF | |
| GGUF is a quantization method that allows you to run large language models on consumer hardware by reducing the precision of the model weights. | |
| ## Files | |
| | Filename | Quant type | File Size | Description | | |
| | -------- | ---------- | --------- | ----------- | | |
| | model-f16.gguf | F16 | Large | Original precision | | |
| | model-q4_0.gguf | Q4_0 | Small | 4-bit quantization | | |
| | model-q4_1.gguf | Q4_1 | Small | 4-bit quantization (higher quality) | | |
| | model-q5_0.gguf | Q5_0 | Medium | 5-bit quantization | | |
| | model-q5_1.gguf | Q5_1 | Medium | 5-bit quantization (higher quality) | | |
| | model-q8_0.gguf | Q8_0 | Large | 8-bit quantization | | |
| ## Usage | |
| You can use these models with llama.cpp or any other GGUF-compatible inference engine. | |
| ### llama.cpp | |
| ```bash | |
| ./llama-cli -m model-q4_0.gguf -p "Your prompt here" | |
| ``` | |
| ### Python (using llama-cpp-python) | |
| ```python | |
| from llama_cpp import Llama | |
| llm = Llama(model_path="model-q4_0.gguf") | |
| output = llm("Your prompt here", max_tokens=512) | |
| print(output['choices'][0]['text']) | |
| ``` | |
| ## Original Model | |
| This is a quantized version of [deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B). Please refer to the original model card for more information about the model's capabilities, training data, and usage guidelines. | |
| ## Conversion Details | |
| - Converted using llama.cpp | |
| - Original model downloaded from Hugging Face | |
| - Multiple quantization levels provided for different use cases | |
| ## License | |
| This model inherits the license from the original model. Please check the original model's license for usage terms. | |