Instructions to use saik0s/comfy_backup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use saik0s/comfy_backup with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="saik0s/comfy_backup", filename="ComfyUI/models/text_encoders/gemma-3-12b-it-q2_k.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use saik0s/comfy_backup 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 saik0s/comfy_backup:Q4_K_S # Run inference directly in the terminal: llama cli -hf saik0s/comfy_backup:Q4_K_S
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf saik0s/comfy_backup:Q4_K_S # Run inference directly in the terminal: llama cli -hf saik0s/comfy_backup:Q4_K_S
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 saik0s/comfy_backup:Q4_K_S # Run inference directly in the terminal: ./llama-cli -hf saik0s/comfy_backup:Q4_K_S
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 saik0s/comfy_backup:Q4_K_S # Run inference directly in the terminal: ./build/bin/llama-cli -hf saik0s/comfy_backup:Q4_K_S
Use Docker
docker model run hf.co/saik0s/comfy_backup:Q4_K_S
- LM Studio
- Jan
- Ollama
How to use saik0s/comfy_backup with Ollama:
ollama run hf.co/saik0s/comfy_backup:Q4_K_S
- Unsloth Studio
How to use saik0s/comfy_backup 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 saik0s/comfy_backup 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 saik0s/comfy_backup to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for saik0s/comfy_backup to start chatting
- Pi
How to use saik0s/comfy_backup with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf saik0s/comfy_backup:Q4_K_S
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "saik0s/comfy_backup:Q4_K_S" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use saik0s/comfy_backup with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf saik0s/comfy_backup:Q4_K_S
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default saik0s/comfy_backup:Q4_K_S
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use saik0s/comfy_backup with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf saik0s/comfy_backup:Q4_K_S
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "saik0s/comfy_backup:Q4_K_S" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
- Docker Model Runner
How to use saik0s/comfy_backup with Docker Model Runner:
docker model run hf.co/saik0s/comfy_backup:Q4_K_S
- Lemonade
How to use saik0s/comfy_backup with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull saik0s/comfy_backup:Q4_K_S
Run and chat with the model
lemonade run user.comfy_backup-Q4_K_S
List all available models
lemonade list
| <template> | |
| <div class="flex h-full flex-col"> | |
| <div class="flex-1 px-4"> | |
| <DataTable :value="sizeList"> | |
| <Column field="name" :header="$t('name')"> | |
| <template #body="{ data, field }"> | |
| {{ $t(data[field]) }} | |
| </template> | |
| </Column> | |
| <Column field="width" :header="$t('width')" class="min-w-36"> | |
| <template #body="{ data, field }"> | |
| <span class="flex items-center gap-4"> | |
| <Slider | |
| v-model="data[field]" | |
| class="flex-1" | |
| v-bind="sizeStint" | |
| ></Slider> | |
| <span>{{ data[field] }}</span> | |
| </span> | |
| </template> | |
| </Column> | |
| <Column field="height" :header="$t('height')" class="min-w-36"> | |
| <template #body="{ data, field }"> | |
| <span class="flex items-center gap-4"> | |
| <Slider | |
| v-model="data[field]" | |
| class="flex-1" | |
| v-bind="sizeStint" | |
| ></Slider> | |
| <span>{{ data[field] }}</span> | |
| </span> | |
| </template> | |
| </Column> | |
| </DataTable> | |
| </div> | |
| <div class="flex justify-between px-4"> | |
| <div></div> | |
| <div class="flex gap-2"> | |
| <Button | |
| icon="pi pi-refresh" | |
| :label="$t('reset')" | |
| @click="handleReset" | |
| ></Button> | |
| <Button :label="$t('cancel')" @click="handleCancelEditor"></Button> | |
| <Button :label="$t('save')" @click="handleSaveSizeMap"></Button> | |
| </div> | |
| </div> | |
| </div> | |
| </template> | |
| <script setup lang="ts"> | |
| import { useConfig } from 'hooks/config' | |
| import { useDialog } from 'hooks/dialog' | |
| import Button from 'primevue/button' | |
| import Column from 'primevue/column' | |
| import DataTable from 'primevue/datatable' | |
| import Slider from 'primevue/slider' | |
| import { onMounted, ref } from 'vue' | |
| const { cardSizeMap, defaultCardSizeMap } = useConfig() | |
| const dialog = useDialog() | |
| const sizeList = ref() | |
| const sizeStint = { | |
| step: 10, | |
| min: 80, | |
| max: 320, | |
| } | |
| const resolveSizeMap = (sizeMap: Record<string, string>) => { | |
| return Object.entries(sizeMap).map(([key, value]) => { | |
| const [width, height] = value.split('x') | |
| return { | |
| id: key, | |
| name: key, | |
| width: parseInt(width), | |
| height: parseInt(height), | |
| } | |
| }) | |
| } | |
| const resolveSizeList = ( | |
| sizeList: { name: string; width: number; height: number }[], | |
| ) => { | |
| return Object.fromEntries( | |
| sizeList.map(({ name, width, height }) => { | |
| return [name, [width, height].join('x')] | |
| }), | |
| ) | |
| } | |
| onMounted(() => { | |
| sizeList.value = resolveSizeMap(cardSizeMap.value) | |
| }) | |
| const handleReset = () => { | |
| sizeList.value = resolveSizeMap(defaultCardSizeMap) | |
| } | |
| const handleCancelEditor = () => { | |
| sizeList.value = resolveSizeMap(cardSizeMap.value) | |
| dialog.close() | |
| } | |
| const handleSaveSizeMap = () => { | |
| cardSizeMap.value = resolveSizeList(sizeList.value) | |
| dialog.close() | |
| } | |
| </script> | |