Text Classification
Safetensors
GGUF
Portuguese
gemma3_text
llama.cpp
unsloth
intent-detection
gemma-3
delivery
conversational
Instructions to use RiosWesley/gemma-3-270M-Model-Router with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use RiosWesley/gemma-3-270M-Model-Router with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="RiosWesley/gemma-3-270M-Model-Router", filename="gemma-3-270m-it.Q8_0.gguf", )
llm.create_chat_completion( messages = "\"I like you. I love you\"" )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use RiosWesley/gemma-3-270M-Model-Router with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf RiosWesley/gemma-3-270M-Model-Router:Q8_0 # Run inference directly in the terminal: llama-cli -hf RiosWesley/gemma-3-270M-Model-Router:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf RiosWesley/gemma-3-270M-Model-Router:Q8_0 # Run inference directly in the terminal: llama-cli -hf RiosWesley/gemma-3-270M-Model-Router:Q8_0
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 RiosWesley/gemma-3-270M-Model-Router:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf RiosWesley/gemma-3-270M-Model-Router:Q8_0
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 RiosWesley/gemma-3-270M-Model-Router:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf RiosWesley/gemma-3-270M-Model-Router:Q8_0
Use Docker
docker model run hf.co/RiosWesley/gemma-3-270M-Model-Router:Q8_0
- LM Studio
- Jan
- Ollama
How to use RiosWesley/gemma-3-270M-Model-Router with Ollama:
ollama run hf.co/RiosWesley/gemma-3-270M-Model-Router:Q8_0
- Unsloth Studio new
How to use RiosWesley/gemma-3-270M-Model-Router with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for RiosWesley/gemma-3-270M-Model-Router to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for RiosWesley/gemma-3-270M-Model-Router to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for RiosWesley/gemma-3-270M-Model-Router to start chatting
- Docker Model Runner
How to use RiosWesley/gemma-3-270M-Model-Router with Docker Model Runner:
docker model run hf.co/RiosWesley/gemma-3-270M-Model-Router:Q8_0
- Lemonade
How to use RiosWesley/gemma-3-270M-Model-Router with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull RiosWesley/gemma-3-270M-Model-Router:Q8_0
Run and chat with the model
lemonade run user.gemma-3-270M-Model-Router-Q8_0
List all available models
lemonade list
Trained with Unsloth - Ollama Modelfile
Browse files
Modelfile
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FROM gemma-3-270m-it.Q8_0.gguf
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TEMPLATE """{{- $systemPromptAdded := false }}
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{{- range $i, $_ := .Messages }}
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{{- $last := eq (len (slice $.Messages $i)) 1 }}
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{{- if eq .Role "user" }}<start_of_turn>user
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{{- if (and (not $systemPromptAdded) $.System) }}
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{{- $systemPromptAdded = true }}
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{{ $.System }}
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{{ end }}
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{{ .Content }}<end_of_turn>
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{{ if $last }}<start_of_turn>model
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{{ end }}
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{{- else if eq .Role "assistant" }}<start_of_turn>model
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{{ .Content }}{{ if not $last }}<end_of_turn>
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{{ end }}
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{{- end }}
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{{- end }}
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"""
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PARAMETER stop "<end_of_turn>"
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PARAMETER top_k 64
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PARAMETER top_p 0.95
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