Instructions to use DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF",
	filename="Ornstein3.6-35B-A3B-RYS-SABER-Q3_K_M.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-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 DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-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 DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF:Q4_K_M

Use Docker

docker model run hf.co/DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-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": "DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF:Q4_K_M

Ollama
How to use DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF with Ollama:
```
ollama run hf.co/DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF:Q4_K_M
```

Unsloth Studio new

How to use DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-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 DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-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 DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF to start chatting

Pi new

How to use DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF:Q4_K_M

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": "DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-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 DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF:Q4_K_M

Run Hermes

hermes

Docker Model Runner
How to use DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF with Docker Model Runner:
```
docker model run hf.co/DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF:Q4_K_M
```

Lemonade

How to use DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Ornstein3.6-35B-A3B-RYS-SABER-GGUF-Q4_K_M

List all available models

lemonade list

crashed

by androidli - opened 28 days ago

Discussion

androidli

28 days ago

Total : 20029.33, 2406.81, 22436.14 MiB
Memory required for model tensors + cache: 22834 MiB
Memory available on all devices - compute: 22799 MiB
llm_load_tensors: ggml ctx size = 0.61 MiB
llama_model_load: error loading model: check_tensor_dims: tensor 'blk.11.attn_q.weight' not found
llama_model_load_from_file: failed to load model
llama_init_from_gpt_params: error: failed to load model 'models/DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF/Ornstein3.6-35B-A3B-RYS-SABER-Q4_K_M.gguf'
ERR [ load_model] unable to load model | tid="127779220193280" timestamp=1776405417 model="models/DJLougen/Ornstein3.6-35B-A3B-RYS-SABER-GGUF/Ornstein3.6-35B-A3B-RYS-SABER-Q4_K_M.gguf"
free(): invalid pointer
Aborted (core dumped)

guiperpt

28 days ago

Same thing here with the Q4_K_S version.

load_tensors: loading model tensors, this can take a while... (mmap = false, direct_io = false)
llama_model_load: error loading model: missing tensor 'blk.11.attn_q.weight'
llama_model_load_from_file_impl: failed to load model

PredragR

28 days ago

•

edited 28 days ago

I can confirm this on latest llama.cpp with Q4_K_M. Everything seems normal on load up to this line where it crashes:
'''
...
create_tensor: loading tensor blk.11.attn_qkv.weight
llama_model_load: error loading model: check_tensor_dims: tensor 'blk.11.attn_qkv.weight' has wrong shape; expected 2048, 9216, got 2048, 8192, 1, 1
llama_model_load_from_file_impl: failed to load model
...
'''

EDIT: Same happens with Q5_K_M. Shame, I really want to try this one out!
EDIT 2: I made my own quant through hf - Q5_K_M from the DJLougen/Ornstein3.6-35B-A3B-RYS-SABER, still not working - the problem is that model, or at the top @DJLougen .

ajs410

28 days ago

•

edited 25 days ago

I'm having the same problem as the others with ollama. Using Q8
source=server.go:1218 msg="llm load error: failed to initialize model: qwen3next: layer 12 missing attn_qkv/attn_gate projections"

Ornstein3.6-35B-A3B-RYS-GGUF also fails, however Ornstein3.6-35B-A3B-SABER-GGUF succeeds.

EDIT: the instructions say we need a special fork of llama.cpp

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