Instructions to use tensorblock/DeepSeek-R1-Distill-Qwen-7B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tensorblock/DeepSeek-R1-Distill-Qwen-7B-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tensorblock/DeepSeek-R1-Distill-Qwen-7B-GGUF", dtype="auto") - MLX
How to use tensorblock/DeepSeek-R1-Distill-Qwen-7B-GGUF with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir DeepSeek-R1-Distill-Qwen-7B-GGUF tensorblock/DeepSeek-R1-Distill-Qwen-7B-GGUF
- llama-cpp-python
How to use tensorblock/DeepSeek-R1-Distill-Qwen-7B-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="tensorblock/DeepSeek-R1-Distill-Qwen-7B-GGUF", filename="DeepSeek-R1-Distill-Qwen-7B-Q2_K.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 tensorblock/DeepSeek-R1-Distill-Qwen-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 tensorblock/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q2_K # Run inference directly in the terminal: llama-cli -hf tensorblock/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf tensorblock/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q2_K # Run inference directly in the terminal: llama-cli -hf tensorblock/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q2_K
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 tensorblock/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q2_K # Run inference directly in the terminal: ./llama-cli -hf tensorblock/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q2_K
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 tensorblock/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf tensorblock/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q2_K
Use Docker
docker model run hf.co/tensorblock/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q2_K
- LM Studio
- Jan
- Ollama
How to use tensorblock/DeepSeek-R1-Distill-Qwen-7B-GGUF with Ollama:
ollama run hf.co/tensorblock/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q2_K
- Unsloth Studio
How to use tensorblock/DeepSeek-R1-Distill-Qwen-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 tensorblock/DeepSeek-R1-Distill-Qwen-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 tensorblock/DeepSeek-R1-Distill-Qwen-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 tensorblock/DeepSeek-R1-Distill-Qwen-7B-GGUF to start chatting
- Docker Model Runner
How to use tensorblock/DeepSeek-R1-Distill-Qwen-7B-GGUF with Docker Model Runner:
docker model run hf.co/tensorblock/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q2_K
- Lemonade
How to use tensorblock/DeepSeek-R1-Distill-Qwen-7B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tensorblock/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q2_K
Run and chat with the model
lemonade run user.DeepSeek-R1-Distill-Qwen-7B-GGUF-Q2_K
List all available models
lemonade list
Upload folder using huggingface_hub
Browse files- DeepSeek-R1-Distill-Qwen-7B-Q2_K.gguf +2 -2
- DeepSeek-R1-Distill-Qwen-7B-Q3_K_L.gguf +2 -2
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- DeepSeek-R1-Distill-Qwen-7B-Q8_0.gguf +2 -2
- README.md +14 -5
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README.md
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---
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base_model:
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tags:
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- TensorBlock
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- GGUF
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---
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</div>
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</div>
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##
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This repo contains GGUF format model files for [
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The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit
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<div style="text-align: left; margin: 20px 0;">
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<a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
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## Prompt template
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```
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<|begin▁of▁sentence|>{system_prompt}<|User|>{prompt}<|Assistant|>
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```
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## Model file specification
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---
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base_model: unsloth/DeepSeek-R1-Distill-Qwen-7B
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language:
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- en
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license: apache-2.0
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library_name: transformers
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tags:
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- deepseek
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- qwen
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- qwen2
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- unsloth
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- transformers
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- TensorBlock
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- GGUF
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---
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</div>
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</div>
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## unsloth/DeepSeek-R1-Distill-Qwen-7B - GGUF
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This repo contains GGUF format model files for [unsloth/DeepSeek-R1-Distill-Qwen-7B](https://huggingface.co/unsloth/DeepSeek-R1-Distill-Qwen-7B).
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The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4823](https://github.com/ggml-org/llama.cpp/commit/5bbe6a9fe9a8796a9389c85accec89dbc4d91e39).
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<div style="text-align: left; margin: 20px 0;">
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<a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
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## Prompt template
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```
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<|begin▁of▁sentence|>{system_prompt}<|User|>{prompt}<|Assistant|><think>
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```
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## Model file specification
|