Instructions to use kanaton/webcoder-t28n with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries
PEFT
How to use kanaton/webcoder-t28n with PEFT:
```
Task type is invalid.
```
Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use kanaton/webcoder-t28n 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 kanaton/webcoder-t28n:Q8_0
# Run inference directly in the terminal:
llama cli -hf kanaton/webcoder-t28n:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf kanaton/webcoder-t28n:Q8_0
# Run inference directly in the terminal:
llama cli -hf kanaton/webcoder-t28n: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 kanaton/webcoder-t28n:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf kanaton/webcoder-t28n: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 kanaton/webcoder-t28n:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf kanaton/webcoder-t28n:Q8_0

Use Docker

docker model run hf.co/kanaton/webcoder-t28n:Q8_0

LM Studio
Jan

vLLM

How to use kanaton/webcoder-t28n with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "kanaton/webcoder-t28n"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "kanaton/webcoder-t28n",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/kanaton/webcoder-t28n:Q8_0

Ollama
How to use kanaton/webcoder-t28n with Ollama:
```
ollama run hf.co/kanaton/webcoder-t28n:Q8_0
```
Unsloth Desktop

How to use kanaton/webcoder-t28n with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf kanaton/webcoder-t28n: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": "kanaton/webcoder-t28n:Q8_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use kanaton/webcoder-t28n with Docker Model Runner:
```
docker model run hf.co/kanaton/webcoder-t28n:Q8_0
```

Lemonade

How to use kanaton/webcoder-t28n with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull kanaton/webcoder-t28n:Q8_0

Run and chat with the model

lemonade run user.webcoder-t28n-Q8_0

List all available models

lemonade list

Hermes Agent

How to use kanaton/webcoder-t28n with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf kanaton/webcoder-t28n: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 kanaton/webcoder-t28n:Q8_0

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use kanaton/webcoder-t28n with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf kanaton/webcoder-t28n: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 "kanaton/webcoder-t28n: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"

WebCoder 1.5B (webcoder-t28n)

Assistant local de développement Web (PHP, HTML, CSS, SQL, JavaScript), adapté par LoRA, fusionné et quantifié en GGUF Q8_0. Conçu pour CPU, sans GPU (cible 8 Go de RAM).

Base : Qwen/Qwen2.5-Coder-1.5B-Instruct (Apache-2.0).
Identité : WebCoder, créé par Pierre Jean Duvivier.
Format : GGUF Q8_0 — webcoder-t28n-q8_0.gguf (~1,65 Gio), pour llama.cpp / llama-server.

Utilisation

llama-server --model webcoder-t28n-q8_0.gguf --ctx-size 4096 --parallel 1 \
  --n-gpu-layers 0 --threads 4 --host 127.0.0.1 --port 8081

Format worker attendu : un bloc file:CHEMIN par fichier modifié (contenu complet).

Limites

Non agentique (pas de tool-calling). Applications web complètes from-scratch : hors de portée.
Code généré non garanti sûr. Licence de base : Apache-2.0.

WebCoder 1.5B (webcoder-t28n) — Pierre Jean Duvivier. Base : Qwen2.5-Coder-1.5B-Instruct (Apache-2.0).

Downloads last month: 13

GGUF

Model size

2B params

Architecture

qwen2

Hardware compatibility

8-bit

Model tree for kanaton/webcoder-t28n

Base model

Qwen/Qwen2.5-1.5B

Finetuned

Qwen/Qwen2.5-Coder-1.5B

Finetuned

Qwen/Qwen2.5-Coder-1.5B-Instruct

Adapter

(194)

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