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 Sep 7

Commit

e5d6131

verified ·

1 Parent(s): 55f1988

Fix Fwizzer-R1.preset.json encoding, system prompt, and reasoning parser

Browse files

Files changed (1) hide show

Fwizzer-R1.preset.json +12 -4

Fwizzer-R1.preset.json CHANGED Viewed

@@ -1,12 +1,12 @@
 {
-  "identifier": "@local:fwizzer-r1",
-  "name": "Fwizzer-R1-3B-RU",
   "changed": true,
   "operation": {
     "fields": [
       {
         "key": "llm.prediction.systemPrompt",
-        "value": "Ты думающая нейросеть а зовут тебя Fwizzer-R1-3B-RU. Весь ход мыслей и шаги пиши внутри тегов <think>(напиши сначала) и </think>(напиши по окончанию рассуждений), а итоговый ответ — обязательно после них."
       },
       {
         "key": "llm.prediction.temperature",
@@ -43,6 +43,14 @@
           "startTag": "<think>",
           "endTag": "</think>"
         }
       }
     ]
   },
@@ -64,4 +72,4 @@
       }
     ]
   }
-}

 {
+  "identifier": "@local:fwizzer-r1-3b-ru",
+  "name": "Fwizzer-R1-3B-RU (Thinking)",
   "changed": true,
   "operation": {
     "fields": [
       {
         "key": "llm.prediction.systemPrompt",
+        "value": "Ты русскоязычный ИИ-ассистент Fwizzer-R1-3B-RU. Твоя задача — рассуждать глубоко и логично внутри тегов <think>(цепочка мыслей) и </think>(ответ пользователю), решая задачи шаг за шагом. Всегда отвечай на русском языке (или на языке запроса пользователя)."
       },
       {
         "key": "llm.prediction.temperature",
           "startTag": "<think>",
           "endTag": "</think>"
         }
+      },
+      {
+        "key": "llm.prediction.stopStrings",
+        "value": [
+          "</s>",
+          "[INST]",
+          "[/INST]"
+        ]
       }
     ]
   },
       }
     ]
   }
+}