Instructions to use hipinis/20260718 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use hipinis/20260718 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 hipinis/20260718:Q8_0
# Run inference directly in the terminal:
llama cli -hf hipinis/20260718:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf hipinis/20260718:Q8_0
# Run inference directly in the terminal:
llama cli -hf hipinis/20260718: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 hipinis/20260718:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf hipinis/20260718: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 hipinis/20260718:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf hipinis/20260718:Q8_0

Use Docker

docker model run hf.co/hipinis/20260718:Q8_0

LM Studio
Jan
Ollama
How to use hipinis/20260718 with Ollama:
```
ollama run hf.co/hipinis/20260718:Q8_0
```
Unsloth Desktop

How to use hipinis/20260718 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf hipinis/20260718:Q8_0

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "hipinis/20260718:Q8_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use hipinis/20260718 with Docker Model Runner:
```
docker model run hf.co/hipinis/20260718:Q8_0
```

Lemonade

How to use hipinis/20260718 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull hipinis/20260718:Q8_0

Run and chat with the model

lemonade run user.20260718-Q8_0

List all available models

lemonade list

Hermes Agent

How to use hipinis/20260718 with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf hipinis/20260718:Q8_0

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 hipinis/20260718:Q8_0

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use hipinis/20260718 with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf hipinis/20260718:Q8_0

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 "hipinis/20260718:Q8_0" \
  --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"

20260718 / custom_nodes /ComfyUI-Custom-Scripts /web /js /showText.js

hipinis

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import { app } from "../../../scripts/app.js";
import { ComfyWidgets } from "../../../scripts/widgets.js";

// Displays input text on a node

// TODO: This should need to be so complicated. Refactor at some point.

app.registerExtension({
	name: "pysssss.ShowText",
	async beforeRegisterNodeDef(nodeType, nodeData, app) {
		if (nodeData.name === "ShowText|pysssss") {
			function populate(text) {
				if (this.widgets) {
					// On older frontend versions there is a hidden converted-widget
					const isConvertedWidget = +!!this.inputs?.[0].widget;
					for (let i = isConvertedWidget; i < this.widgets.length; i++) {
						this.widgets[i].onRemove?.();
					}
					this.widgets.length = isConvertedWidget;
				}

				const v = [...text];
				if (!v[0]) {
					v.shift();
				}
				for (let list of v) {
					// Force list to be an array, not sure why sometimes it is/isn't
					if (!(list instanceof Array)) list = [list];
					for (const l of list) {
						const w = ComfyWidgets["STRING"](this, "text_" + this.widgets?.length ?? 0, ["STRING", { multiline: true }], app).widget;
						w.inputEl.readOnly = true;
						w.inputEl.style.opacity = 0.6;
						w.value = l;
					}
				}

				requestAnimationFrame(() => {
					const sz = this.computeSize();
					if (sz[0] < this.size[0]) {
						sz[0] = this.size[0];
					}
					if (sz[1] < this.size[1]) {
						sz[1] = this.size[1];
					}
					this.onResize?.(sz);
					app.graph.setDirtyCanvas(true, false);
				});
			}

			// When the node is executed we will be sent the input text, display this in the widget
			const onExecuted = nodeType.prototype.onExecuted;
			nodeType.prototype.onExecuted = function (message) {
				onExecuted?.apply(this, arguments);
				populate.call(this, message.text);
			};

			const VALUES = Symbol();
			const configure = nodeType.prototype.configure;
			nodeType.prototype.configure = function () {
				// Store unmodified widget values as they get removed on configure by new frontend
				this[VALUES] = arguments[0]?.widgets_values;
				return configure?.apply(this, arguments);
			};

			const onConfigure = nodeType.prototype.onConfigure;
			nodeType.prototype.onConfigure = function () {
				onConfigure?.apply(this, arguments);
				const widgets_values = this[VALUES];
				if (widgets_values?.length) {
					// In newer frontend there seems to be a delay in creating the initial widget
					requestAnimationFrame(() => {
						populate.call(this, widgets_values.slice(+(widgets_values.length > 1 && this.inputs?.[0].widget)));
					});
				}
			};
		}
	},
});

	import { app } from "../../../scripts/app.js";
	import { ComfyWidgets } from "../../../scripts/widgets.js";

	// Displays input text on a node

	// TODO: This should need to be so complicated. Refactor at some point.

	app.registerExtension({
	name: "pysssss.ShowText",
	async beforeRegisterNodeDef(nodeType, nodeData, app) {
	if (nodeData.name === "ShowText\|pysssss") {
	function populate(text) {
	if (this.widgets) {
	// On older frontend versions there is a hidden converted-widget
	const isConvertedWidget = +!!this.inputs?.[0].widget;
	for (let i = isConvertedWidget; i < this.widgets.length; i++) {
	this.widgets[i].onRemove?.();
	}
	this.widgets.length = isConvertedWidget;
	}

	const v = [...text];
	if (!v[0]) {
	v.shift();
	}
	for (let list of v) {
	// Force list to be an array, not sure why sometimes it is/isn't
	if (!(list instanceof Array)) list = [list];
	for (const l of list) {
	const w = ComfyWidgets["STRING"](this, "text_" + this.widgets?.length ?? 0, ["STRING", { multiline: true }], app).widget;
	w.inputEl.readOnly = true;
	w.inputEl.style.opacity = 0.6;
	w.value = l;
	}
	}

	requestAnimationFrame(() => {
	const sz = this.computeSize();
	if (sz[0] < this.size[0]) {
	sz[0] = this.size[0];
	}
	if (sz[1] < this.size[1]) {
	sz[1] = this.size[1];
	}
	this.onResize?.(sz);
	app.graph.setDirtyCanvas(true, false);
	});
	}

	// When the node is executed we will be sent the input text, display this in the widget
	const onExecuted = nodeType.prototype.onExecuted;
	nodeType.prototype.onExecuted = function (message) {
	onExecuted?.apply(this, arguments);
	populate.call(this, message.text);
	};

	const VALUES = Symbol();
	const configure = nodeType.prototype.configure;
	nodeType.prototype.configure = function () {
	// Store unmodified widget values as they get removed on configure by new frontend
	this[VALUES] = arguments[0]?.widgets_values;
	return configure?.apply(this, arguments);
	};

	const onConfigure = nodeType.prototype.onConfigure;
	nodeType.prototype.onConfigure = function () {
	onConfigure?.apply(this, arguments);
	const widgets_values = this[VALUES];
	if (widgets_values?.length) {
	// In newer frontend there seems to be a delay in creating the initial widget
	requestAnimationFrame(() => {
	populate.call(this, widgets_values.slice(+(widgets_values.length > 1 && this.inputs?.[0].widget)));
	});
	}
	};
	}
	},
	});