Instructions to use WildOjisan/gemma-3-270mit-finetune-Q4_k_m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use WildOjisan/gemma-3-270mit-finetune-Q4_k_m 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 WildOjisan/gemma-3-270mit-finetune-Q4_k_m:Q4_K_M # Run inference directly in the terminal: llama cli -hf WildOjisan/gemma-3-270mit-finetune-Q4_k_m:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf WildOjisan/gemma-3-270mit-finetune-Q4_k_m:Q4_K_M # Run inference directly in the terminal: llama cli -hf WildOjisan/gemma-3-270mit-finetune-Q4_k_m: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 WildOjisan/gemma-3-270mit-finetune-Q4_k_m:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf WildOjisan/gemma-3-270mit-finetune-Q4_k_m: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 WildOjisan/gemma-3-270mit-finetune-Q4_k_m:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf WildOjisan/gemma-3-270mit-finetune-Q4_k_m:Q4_K_M
Use Docker
docker model run hf.co/WildOjisan/gemma-3-270mit-finetune-Q4_k_m:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use WildOjisan/gemma-3-270mit-finetune-Q4_k_m with Ollama:
ollama run hf.co/WildOjisan/gemma-3-270mit-finetune-Q4_k_m:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use WildOjisan/gemma-3-270mit-finetune-Q4_k_m with Docker Model Runner:
docker model run hf.co/WildOjisan/gemma-3-270mit-finetune-Q4_k_m:Q4_K_M
- Lemonade
How to use WildOjisan/gemma-3-270mit-finetune-Q4_k_m with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull WildOjisan/gemma-3-270mit-finetune-Q4_k_m:Q4_K_M
Run and chat with the model
lemonade run user.gemma-3-270mit-finetune-Q4_k_m-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download Modelfile from WildOjisan/gemma-3-270mit-finetune-Q4_k_m: direct link, hf CLI and curl.
- Browser
- Download file 597 Bytes
-
https://huggingface.co/WildOjisan/gemma-3-270mit-finetune-Q4_k_m/resolve/main/Modelfile
- Command line
-
hf download hf://WildOjisan/gemma-3-270mit-finetune-Q4_k_m/Modelfile
-
curl -L -o Modelfile https://huggingface.co/WildOjisan/gemma-3-270mit-finetune-Q4_k_m/resolve/main/Modelfile
597 Bytes
| FROM gemma-3-270m-it.Q4_K_M.gguf | |
| TEMPLATE """{{- $systemPromptAdded := false }} | |
| {{- range $i, $_ := .Messages }} | |
| {{- $last := eq (len (slice $.Messages $i)) 1 }} | |
| {{- if eq .Role "user" }}<start_of_turn>user | |
| {{- if (and (not $systemPromptAdded) $.System) }} | |
| {{- $systemPromptAdded = true }} | |
| {{ $.System }} | |
| {{ end }} | |
| {{ .Content }}<end_of_turn> | |
| {{ if $last }}<start_of_turn>model | |
| {{ end }} | |
| {{- else if eq .Role "assistant" }}<start_of_turn>model | |
| {{ .Content }}{{ if not $last }}<end_of_turn> | |
| {{ end }} | |
| {{- end }} | |
| {{- end }} | |
| """ | |
| PARAMETER stop "<end_of_turn>" | |
| PARAMETER top_k 64 | |
| PARAMETER top_p 0.95 |