Text Generation
GGUF
English
qwen3_5_text
27b
stem
tutor
math
physics
chemistry
biology
computer-science
claude-distillation
conversational
local
offline
lm-studio
llama-cpp
Instructions to use Verdugie/STEM-Oracle 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 Verdugie/STEM-Oracle 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 Verdugie/STEM-Oracle:Q4_K_M # Run inference directly in the terminal: llama cli -hf Verdugie/STEM-Oracle:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Verdugie/STEM-Oracle:Q4_K_M # Run inference directly in the terminal: llama cli -hf Verdugie/STEM-Oracle: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 Verdugie/STEM-Oracle:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Verdugie/STEM-Oracle: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 Verdugie/STEM-Oracle:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Verdugie/STEM-Oracle:Q4_K_M
Use Docker
docker model run hf.co/Verdugie/STEM-Oracle:Q4_K_M
- Llama new
- LM Studio
- Jan
- vLLM
How to use Verdugie/STEM-Oracle with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Verdugie/STEM-Oracle" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Verdugie/STEM-Oracle", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Verdugie/STEM-Oracle:Q4_K_M
- Ollama
How to use Verdugie/STEM-Oracle with Ollama:
ollama run hf.co/Verdugie/STEM-Oracle:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use Verdugie/STEM-Oracle with Docker Model Runner:
docker model run hf.co/Verdugie/STEM-Oracle:Q4_K_M
- Lemonade
How to use Verdugie/STEM-Oracle with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Verdugie/STEM-Oracle:Q4_K_M
Run and chat with the model
lemonade run user.STEM-Oracle-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Commit History
Today
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Clean .gitattributes: generic LFS patterns, drop stale per-file entries
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Card rewrite: uniform structure, renamed files, sidecar cleanup
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chore: bump for profile ordering
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Full BF16 GGUF - STEM Oracle 27B
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Full BF16 merged weights — STEM Oracle 27B (LoRA r=128, 3224 conv, 4 epochs)
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Restore deleted files (GGUFs, training data, .gitattributes)
Files were accidentally removed during a card update that used git add . without LFS objects present. Restoring from git history.4e96fc6 -
Add architecture spec paper link in Dataset section
Verdugie9a82763
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V3.5 Q8_0 — density-optimized 27B (5,358 conv, LoRA r=128)
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V3.5 Q6_K — density-optimized 27B (5,358 conv, LoRA r=128)
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V3.5 Q4_K_M — density-optimized 27B (5,358 conv, LoRA r=128)
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initial commit
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