Instructions to use fwizzer1/Fwizzer-R1-3B-RU with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use fwizzer1/Fwizzer-R1-3B-RU 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 fwizzer1/Fwizzer-R1-3B-RU
# Run inference directly in the terminal:
llama cli -hf fwizzer1/Fwizzer-R1-3B-RU

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf fwizzer1/Fwizzer-R1-3B-RU
# Run inference directly in the terminal:
llama cli -hf fwizzer1/Fwizzer-R1-3B-RU

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 fwizzer1/Fwizzer-R1-3B-RU
# Run inference directly in the terminal:
./llama-cli -hf fwizzer1/Fwizzer-R1-3B-RU

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 fwizzer1/Fwizzer-R1-3B-RU
# Run inference directly in the terminal:
./build/bin/llama-cli -hf fwizzer1/Fwizzer-R1-3B-RU

Use Docker

docker model run hf.co/fwizzer1/Fwizzer-R1-3B-RU

LM Studio
Jan

vLLM

How to use fwizzer1/Fwizzer-R1-3B-RU with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "fwizzer1/Fwizzer-R1-3B-RU"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "fwizzer1/Fwizzer-R1-3B-RU",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/fwizzer1/Fwizzer-R1-3B-RU

Ollama
How to use fwizzer1/Fwizzer-R1-3B-RU with Ollama:
```
ollama run hf.co/fwizzer1/Fwizzer-R1-3B-RU
```
Unsloth Desktop
Docker Model Runner
How to use fwizzer1/Fwizzer-R1-3B-RU with Docker Model Runner:
```
docker model run hf.co/fwizzer1/Fwizzer-R1-3B-RU
```

Lemonade

How to use fwizzer1/Fwizzer-R1-3B-RU with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull fwizzer1/Fwizzer-R1-3B-RU

Run and chat with the model

lemonade run user.Fwizzer-R1-3B-RU-{{QUANT_TAG}}

List all available models

lemonade list

Atomic Chat

fwizzer1 commited on Aug 30

Commit

e5e58be

verified ·

1 Parent(s): 6c47f38

Add README

Browse files

Files changed (1) hide show

README.md +12 -13

README.md CHANGED Viewed

@@ -1,22 +1,21 @@
 ---
-base_model: unsloth/Ministral-3-3B-Instruct-2512-bnb-4bit
 tags:
-- text-generation-inference
-- transformers
 - unsloth
-- mistral3
-- trl
-license: apache-2.0
-language:
-- en
 ---
-# Uploaded  model
-- **Developed by:** fwizzer1
-- **License:** apache-2.0
-- **Finetuned from model :** unsloth/Ministral-3-3B-Instruct-2512-bnb-4bit
-This mistral3 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth)
 [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

 ---
 tags:
+- gguf
+- llama.cpp
 - unsloth
 ---
+# ministral-3b-reasoning-ru : GGUF
+This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).
+**Example usage**:
+- For text only LLMs:    `llama-cli -hf fwizzer1/ministral-3b-reasoning-ru --jinja`
+- For multimodal models: `llama-mtmd-cli -hf fwizzer1/ministral-3b-reasoning-ru --jinja`
+## Available Model files:
+- `Ministral-3-3B-Instruct-2512.Q8_0.gguf`
+- `Ministral-3-3B-Instruct-2512.Q4_K_M.gguf`
+This was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth)
 [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)