Text Generation
Safetensors
GGUF
English
qwen2
deepseek
deepseek-r1
desyced
anti-sycophancy
conversational
Instructions to use ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced 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 ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced:Q4_K_M # Run inference directly in the terminal: llama cli -hf ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced:Q4_K_M # Run inference directly in the terminal: llama cli -hf ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced: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 ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced: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 ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced:Q4_K_M
Use Docker
docker model run hf.co/ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced:Q4_K_M
- Ollama
How to use ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced with Ollama:
ollama run hf.co/ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced:Q4_K_M
- Unsloth Studio
How to use ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced 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 ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced 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 ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced to start chatting
- Atomic Chat new
- Docker Model Runner
How to use ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced with Docker Model Runner:
docker model run hf.co/ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced:Q4_K_M
- Lemonade
How to use ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ApolloRaines/DeepSeek-R1-Distill-Qwen-7B-Desyced:Q4_K_M
Run and chat with the model
lemonade run user.DeepSeek-R1-Distill-Qwen-7B-Desyced-Q4_K_M
List all available models
lemonade list
File size: 704 Bytes
3c09bfd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | {
"architectures": [
"Qwen2ForCausalLM"
],
"attention_dropout": 0.0,
"bos_token_id": 151643,
"eos_token_id": 151643,
"hidden_act": "silu",
"hidden_size": 3584,
"initializer_range": 0.02,
"intermediate_size": 18944,
"max_position_embeddings": 131072,
"max_window_layers": 28,
"model_type": "qwen2",
"num_attention_heads": 28,
"num_hidden_layers": 28,
"num_key_value_heads": 4,
"rms_norm_eps": 1e-06,
"rope_scaling": null,
"rope_theta": 10000,
"sliding_window": 4096,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"transformers_version": "4.51.3",
"use_cache": true,
"use_mrope": false,
"use_sliding_window": false,
"vocab_size": 152064
}
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