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

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

STEM-Oracle / transcripts /computer-science.pdf

Verdugie

Explainer card with a five-subject battery and transcripts

37f9a8c verified about 7 hours ago

History Blame Contribute Delete

43.2 kB

Xet Pointer Details

( Raw pointer file )

Xet hash:: bf3c45109f4ed4616d45634469146369eeb35e2c08147d44a9c1916b8d2ab259
Size of remote file:: 43.2 kB
SHA256:: 284b340900be5fe0fc14ce2c075f2532d2ae86d6e25baf689dbb56ddc3c86bed

Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.