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

Llama new
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 29

Commit

5e623ca

verified ·

1 Parent(s): d60f742

Upload model trained with Unsloth

Browse files

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Files changed (4) hide show

.gitattributes +1 -0
chat_template.jinja +1 -0
tokenizer.json +3 -0
tokenizer_config.json +0 -0

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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
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chat_template.jinja ADDED Viewed

	@@ -0,0 +1 @@

+ {{ bos_token }}{% if messages[0]['role'] == 'system' %}{% if messages[1]['role'] == 'user' %}{{ '[INST] ' + messages[0]['content'] + ' ' + messages[1]['content'] + ' [/INST]' }}{% set loop_messages = messages[2:] %}{% else %}{{ '[INST] ' + messages[0]['content'] + ' [/INST]' }}{% set loop_messages = messages[1:] %}{% endif %}{% else %}{% set loop_messages = messages %}{% endif %}{% for message in loop_messages %}{% if message['role'] == 'user' %}{{ '[INST] ' + message['content'] + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ message['content'] + eos_token }}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}

tokenizer.json ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:1f618544fe5e621621e6f93d93a95992fd59fd7ffa8c94be0cf21a3e13b38d32
+size 17078209

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