Text Generation
PEFT
Safetensors
GGUF
Italian
lira
lora
personal-finance
retrieval-augmented-generation
readability
italian
conversational
Instructions to use Stee201/lira-gemma3-1b-ita-sipar-3reg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Stee201/lira-gemma3-1b-ita-sipar-3reg with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-3-1b-it") model = PeftModel.from_pretrained(base_model, "Stee201/lira-gemma3-1b-ita-sipar-3reg") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Stee201/lira-gemma3-1b-ita-sipar-3reg 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 Stee201/lira-gemma3-1b-ita-sipar-3reg:Q4_K_M # Run inference directly in the terminal: llama cli -hf Stee201/lira-gemma3-1b-ita-sipar-3reg:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Stee201/lira-gemma3-1b-ita-sipar-3reg:Q4_K_M # Run inference directly in the terminal: llama cli -hf Stee201/lira-gemma3-1b-ita-sipar-3reg: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 Stee201/lira-gemma3-1b-ita-sipar-3reg:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Stee201/lira-gemma3-1b-ita-sipar-3reg: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 Stee201/lira-gemma3-1b-ita-sipar-3reg:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Stee201/lira-gemma3-1b-ita-sipar-3reg:Q4_K_M
Use Docker
docker model run hf.co/Stee201/lira-gemma3-1b-ita-sipar-3reg:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use Stee201/lira-gemma3-1b-ita-sipar-3reg with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Stee201/lira-gemma3-1b-ita-sipar-3reg" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Stee201/lira-gemma3-1b-ita-sipar-3reg", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Stee201/lira-gemma3-1b-ita-sipar-3reg:Q4_K_M
- Ollama
How to use Stee201/lira-gemma3-1b-ita-sipar-3reg with Ollama:
ollama run hf.co/Stee201/lira-gemma3-1b-ita-sipar-3reg:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use Stee201/lira-gemma3-1b-ita-sipar-3reg with Docker Model Runner:
docker model run hf.co/Stee201/lira-gemma3-1b-ita-sipar-3reg:Q4_K_M
- Lemonade
How to use Stee201/lira-gemma3-1b-ita-sipar-3reg with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Stee201/lira-gemma3-1b-ita-sipar-3reg:Q4_K_M
Run and chat with the model
lemonade run user.lira-gemma3-1b-ita-sipar-3reg-Q4_K_M
List all available models
lemonade list
- Atomic Chat
| {{ bos_token }} | |
| {%- if messages[0]['role'] == 'system' -%} | |
| {%- if messages[0]['content'] is string -%} | |
| {%- set first_user_prefix = messages[0]['content'] + ' | |
| ' -%} | |
| {%- else -%} | |
| {%- set first_user_prefix = messages[0]['content'][0]['text'] + ' | |
| ' -%} | |
| {%- endif -%} | |
| {%- set loop_messages = messages[1:] -%} | |
| {%- else -%} | |
| {%- set first_user_prefix = "" -%} | |
| {%- set loop_messages = messages -%} | |
| {%- endif -%} | |
| {%- for message in loop_messages -%} | |
| {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%} | |
| {{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }} | |
| {%- endif -%} | |
| {%- if (message['role'] == 'assistant') -%} | |
| {%- set role = "model" -%} | |
| {%- else -%} | |
| {%- set role = message['role'] -%} | |
| {%- endif -%} | |
| {{ '<start_of_turn>' + role + ' | |
| ' + (first_user_prefix if loop.first else "") }} | |
| {%- if message['content'] is string -%} | |
| {{ message['content'] | trim }} | |
| {%- elif message['content'] is iterable -%} | |
| {%- for item in message['content'] -%} | |
| {%- if item['type'] == 'image' -%} | |
| {{ '<start_of_image>' }} | |
| {%- elif item['type'] == 'text' -%} | |
| {{ item['text'] | trim }} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {%- else -%} | |
| {{ raise_exception("Invalid content type") }} | |
| {%- endif -%} | |
| {{ '<end_of_turn> | |
| ' }} | |
| {%- endfor -%} | |
| {%- if add_generation_prompt -%} | |
| {{'<start_of_turn>model | |
| '}} | |
| {%- endif -%} | |