Instructions to use PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion 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 PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion:Q4_K_M

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama cli -hf PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion:Q4_K_M

Use Docker

docker model run hf.co/PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion:Q4_K_M

Llama new
LM Studio
Jan

vLLM

How to use PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion:Q4_K_M

Ollama
How to use PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion with Ollama:
```
ollama run hf.co/PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion:Q4_K_M
```
Unsloth Desktop

How to use PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion:Q4_K_M

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": "PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion with Docker Model Runner:
```
docker model run hf.co/PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion:Q4_K_M
```

Lemonade

How to use PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion:Q4_K_M

Run and chat with the model

lemonade run user.Qwen-Coder-1.5B_Q4_K_M_full_line_completion-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion:Q4_K_M

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 PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion:Q4_K_M

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 "PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion:Q4_K_M" \
  --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"

Qwen-Coder-1.5B_Q4_K_M_full_line_completion / README.md

Zemder

Write README.md and model manifest file

fdea0f6 verified 2 days ago

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---
license: lgpl-3.0
base_model: Qwen/Qwen2.5-Coder-1.5B
pipeline_tag: text-generation
tags:
  - gguf
  - pascal
  - code-completion
---
# PascalABC.NET Full Line Completion (Qwen/Qwen2.5-Coder-1.5B, Q4_K_M)

FIM (fill-in-the-middle) model fine-tuned for full-line code completion in
PascalABC.NET. Runs locally via llama.cpp (`llama-server`) and powers the AI
full-line completion (ghost text) feature of the PascalABC.NET VS Code
extension.

- **Base model:** Qwen/Qwen2.5-Coder-1.5B
- **Quantization:** Q4_K_M — `completion_qwen_pascal_q4_k_m.gguf` (~940 MiB)
- **Intended use:** short inline suggestions while typing PascalABC.NET code
- **Language:** Pascal (PascalABC.NET dialect)
- **Limitations:** a 1.5B model — expect short, conservative completions;
  Pascal sources only; everything runs offline on the user's machine

## Usage

Installed automatically by the PascalABC.NET VS Code extension
(setting `pascalabc.fullLineCompletion.enabled`), or manually:

```
dotnet FullLineCompletionSetup.dll --model-url https://huggingface.co/PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion/resolve/<revision>/completion_qwen_pascal_q4_k_m.gguf
```

## Versioning

The immutable model version is the git revision (commit SHA) of this
repository. `fullline-model.json` in the repository root records the current
version (file name, revision, sha256, size) and is the integration point for
tooling that needs to check for updates.

## License

LGPL-3.0, the same as PascalABC.NET tooling.

	---
	license: lgpl-3.0
	base_model: Qwen/Qwen2.5-Coder-1.5B
	pipeline_tag: text-generation
	tags:
	- gguf
	- pascal
	- code-completion
	---

	# PascalABC.NET Full Line Completion (Qwen/Qwen2.5-Coder-1.5B, Q4_K_M)

	FIM (fill-in-the-middle) model fine-tuned for full-line code completion in
	PascalABC.NET. Runs locally via llama.cpp (`llama-server`) and powers the AI
	full-line completion (ghost text) feature of the PascalABC.NET VS Code
	extension.

	- Base model: Qwen/Qwen2.5-Coder-1.5B
	- Quantization: Q4_K_M — `completion_qwen_pascal_q4_k_m.gguf` (~940 MiB)
	- Intended use: short inline suggestions while typing PascalABC.NET code
	- Language: Pascal (PascalABC.NET dialect)
	- Limitations: a 1.5B model — expect short, conservative completions;
	Pascal sources only; everything runs offline on the user's machine

	## Usage

	Installed automatically by the PascalABC.NET VS Code extension
	(setting `pascalabc.fullLineCompletion.enabled`), or manually:

	```
	dotnet FullLineCompletionSetup.dll --model-url https://huggingface.co/PascalABCNET/Qwen-Coder-1.5B_Q4_K_M_full_line_completion/resolve/<revision>/completion_qwen_pascal_q4_k_m.gguf
	```

	## Versioning

	The immutable model version is the git revision (commit SHA) of this
	repository. `fullline-model.json` in the repository root records the current
	version (file name, revision, sha256, size) and is the integration point for
	tooling that needs to check for updates.

	## License

	LGPL-3.0, the same as PascalABC.NET tooling.