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

Verdugie commited on about 12 hours ago

Commit

3e09e4e

verified ·

1 Parent(s): 5133652

Card: independent description, short battery results, family index

Browse files

Files changed (1) hide show

README.md +5 -5

README.md CHANGED Viewed

@@ -28,7 +28,7 @@ pipeline_tag: text-generation
 ## STEM Oracle
-A STEM tutoring model fine-tuned from Qwen 3.5 27B on **5,179 conversations**. In the Candid line it is the STEM tutor, beside Candid 3.5. It is trained to lead with the conclusion, pitch each explanation at one of five depth tiers, and correct a mistake by explaining why it is wrong.
 By the training file's source tags, about half of the data was written by Claude Haiku and a small share by Claude Opus, a fifth was enhanced by Claude Sonnet, and over a third carries no model tag.
@@ -77,10 +77,10 @@ Thinking: the two shipped templates disagree. `chat_template.jinja` opens a `<th
 ## The Candid Line
-| Model | Size | For | Status |
-|-------|------|-----|--------|
-| [Candid 3.5](https://huggingface.co/Verdugie/Candid-3.5) | 27B | conversation, opinion, pushback; EN/ES | current release |
-| **STEM Oracle** (this model) | 27B | STEM tutoring | available |
 ## Dataset

 ## STEM Oracle
+A STEM tutoring model fine-tuned from Qwen 3.5 27B on **5,179 conversations**. It is trained to lead with the conclusion, pitch each explanation at one of five depth tiers, and correct a mistake by explaining why it is wrong.
 By the training file's source tags, about half of the data was written by Claude Haiku and a small share by Claude Opus, a fifth was enhanced by Claude Sonnet, and over a third carries no model tag.
 ## The Candid Line
+| Model | Size | For |
+|-------|------|-----|
+| [Candid 3.5](https://huggingface.co/Verdugie/Candid-3.5) | 27B | conversation, opinion, pushback; EN/ES |
+| **STEM Oracle** (this model) | 27B | STEM tutoring |
 ## Dataset