Instructions to use tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF 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 tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF: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 tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF: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 tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF:Q4_K_M

Use Docker

docker model run hf.co/tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF:Q4_K_M

Ollama
How to use tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF with Ollama:
```
ollama run hf.co/tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF:Q4_K_M
```

Unsloth Studio

How to use tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF 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 tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF 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 tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF to start chatting

How to use tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF: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": "tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF with Docker Model Runner:
```
docker model run hf.co/tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF:Q4_K_M
```

Lemonade

How to use tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF: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 tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF: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 "tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF: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"

MTP layers

by felkf - opened Jul 15

Discussion

felkf

Jul 15

Was the MTP layer trained jointly with the model, or was it just added after mergeing?

tepirale

Owner Jul 15

Hi, I don't train these models; I use MergeKit with Dare-Ties and modify the code to improve the algorithm without training the model. After obtaining the new LLM model, I extract the MTP and implant a new MTP model, which would be 'official Qwen3.6-35B-A3B GGUF'. In version 2, I implant another MTP model. With each MTP implant, I modify certain layers to improve accuracy.

felkf

Jul 16

Could you upload this model in Hugging Face format (safetensors) as well? I really want to convert it to MLX format to run on Apple Silicon. Thank you!

felkf changed discussion status to closed Jul 16

tepirale

Owner Jul 16

https://huggingface.co/tepirale/Ornith-Agents-A1-3.6-35B-A3B-dare_ties/tree/main

felkf

Jul 16

but there is no mtp layers info in model.safetensors.index.json file

tepirale

Owner Jul 16

If that's the case, then I made a mistake; I would have to review the code and I don't have it on hand.

tepirale

Owner Jul 16

Hi, after reviewing the code you're absolutely right, safetensors doesn't have the MTP graft, but GGUF does at layer 40. I need to correct that since I never added the flag. Thank you very much.

tepirale

Owner Jul 16

Luckily I named the model 'tepirale/Ornith-Agents-A1-3.6-35B-A3B-dare_ties' and not 'tepirale/Ornith-Agents-A1-3.6-35B-A3B-dare_ties-MTP', I need to create a model 'tepirale/Ornith-Agents-A1-3.6-35B-A3B-dare_ties-MTP'

gguf models without problems

It has integrated MTP

https://huggingface.co/tepirale/Ornith-Agents-A1-3.6-35B-A3B-MTP-GGUF/blob/main/Ornith-Agents-A1-3.6-35B-A3B-dare_ties-Q8_0.gguf

felkf

Jul 16

Yes! that a point

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