Instructions to use vanpelt/summarizer 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 vanpelt/summarizer 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 vanpelt/summarizer:Q4_K_M # Run inference directly in the terminal: llama cli -hf vanpelt/summarizer:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf vanpelt/summarizer:Q4_K_M # Run inference directly in the terminal: llama cli -hf vanpelt/summarizer: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 vanpelt/summarizer:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf vanpelt/summarizer: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 vanpelt/summarizer:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf vanpelt/summarizer:Q4_K_M
Use Docker
docker model run hf.co/vanpelt/summarizer:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use vanpelt/summarizer with Ollama:
ollama run hf.co/vanpelt/summarizer:Q4_K_M
- Unsloth Studio
How to use vanpelt/summarizer 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 vanpelt/summarizer 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 vanpelt/summarizer to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for vanpelt/summarizer to start chatting
- Atomic Chat new
- Docker Model Runner
How to use vanpelt/summarizer with Docker Model Runner:
docker model run hf.co/vanpelt/summarizer:Q4_K_M
- Lemonade
How to use vanpelt/summarizer with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull vanpelt/summarizer:Q4_K_M
Run and chat with the model
lemonade run user.summarizer-Q4_K_M
List all available models
lemonade list
File size: 1,108 Bytes
8a6e45b 59e78da bd35c35 59e78da bd35c35 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | FROM gemma3-270m-summarizer-Q4_K_M.gguf
# Default system prompt (used when user doesn't provide one)
SYSTEM """
You are a careful assistant that outputs ONLY valid JSON matching the schema:
{
"summary": "<2-4 words, Title Case, no punctuation>",
"branch": "<kebab-case, lowercase, [a-z0-9-] only, max 3 words, prefix with a category like bug/, feat/, etc.>"
}
Never include explanations or extra keys.
Turn this request for code changes into:
1) a 2-4 word summary (Title Case),
2) a friendly git branch name (prefixed kebab-case).
"""
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
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