Instructions to use gbuzhf/SNEX-V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use gbuzhf/SNEX-V1 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 gbuzhf/SNEX-V1:BF16
# Run inference directly in the terminal:
llama cli -hf gbuzhf/SNEX-V1:BF16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf gbuzhf/SNEX-V1:BF16
# Run inference directly in the terminal:
llama cli -hf gbuzhf/SNEX-V1:BF16

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 gbuzhf/SNEX-V1:BF16
# Run inference directly in the terminal:
./build/bin/llama cli -hf gbuzhf/SNEX-V1:BF16

Use Docker

docker model run hf.co/gbuzhf/SNEX-V1:BF16

Llama new
LM Studio
Jan

vLLM

How to use gbuzhf/SNEX-V1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "gbuzhf/SNEX-V1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "gbuzhf/SNEX-V1",
		"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/gbuzhf/SNEX-V1:BF16

Ollama
How to use gbuzhf/SNEX-V1 with Ollama:
```
ollama run hf.co/gbuzhf/SNEX-V1:BF16
```
Unsloth Desktop

How to use gbuzhf/SNEX-V1 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf gbuzhf/SNEX-V1:BF16

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": "gbuzhf/SNEX-V1:BF16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use gbuzhf/SNEX-V1 with Docker Model Runner:
```
docker model run hf.co/gbuzhf/SNEX-V1:BF16
```

Lemonade

How to use gbuzhf/SNEX-V1 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull gbuzhf/SNEX-V1:BF16

Run and chat with the model

lemonade run user.SNEX-V1-BF16

List all available models

lemonade list

Hermes Agent

How to use gbuzhf/SNEX-V1 with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf gbuzhf/SNEX-V1:BF16

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 gbuzhf/SNEX-V1:BF16

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use gbuzhf/SNEX-V1 with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf gbuzhf/SNEX-V1:BF16

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 "gbuzhf/SNEX-V1:BF16" \
  --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"

gbuzhf commited on 6 days ago

Commit

2a4c5ca

verified ·

1 Parent(s): 82c5d9c

card: experimental-merge note; remove benchmark lineage charts

Browse files

Files changed (3) hide show

README.md +1 -3
assets/SNEX-V1_benchmarks_full.png +0 -3
assets/SNEX-V1_benchmarks_small.png +0 -3

README.md CHANGED Viewed

@@ -32,9 +32,7 @@ the vision projector, the MTP draft head, the router, the norms, the embeddings.
 | Donor | [nex-agi/Nex-N2.5-mini](https://huggingface.co/nex-agi/Nex-N2.5-mini) (only its delta from [Qwen/Qwen3.5-35B-A3B](https://huggingface.co/Qwen/Qwen3.5-35B-A3B)) |
 | Chat template | Arrow 4.0-snex (`qwen3.8-sharp-v22.5.0-arrow4.0-snex`), embedded in every file |
-![SNEX-V1 lineage on the benchmarks](assets/SNEX-V1_benchmarks_small.png)
-*The weaknesses of Sage-A1.5 have been addressed and strengthened. By refining the differences relative to Nex’s own base model (Qwen 3.5 35B-A3B), 75% of the "delta energy" (the differential) was successfully transplanted into Sage. Since the Sage base remained frozen during this process, no regression occurred. The model is exceptionally consistent. Furthermore, the distinct styles of reasoning, behavior, and language usage between Nex and Sage have been reconciled and bridged using a customized Arrow4.0 template.*
 ## Fidelity of the ICE 2.0 tiers (vs the BF16 master)

 | Donor | [nex-agi/Nex-N2.5-mini](https://huggingface.co/nex-agi/Nex-N2.5-mini) (only its delta from [Qwen/Qwen3.5-35B-A3B](https://huggingface.co/Qwen/Qwen3.5-35B-A3B)) |
 | Chat template | Arrow 4.0-snex (`qwen3.8-sharp-v22.5.0-arrow4.0-snex`), embedded in every file |
+*An experimental merge: it is not claimed or shown to improve on Sage-A1.5.*
 ## Fidelity of the ICE 2.0 tiers (vs the BF16 master)

assets/SNEX-V1_benchmarks_full.png DELETED Viewed

Git LFS Details

SHA256: dc672bf302525612e63405802b13bd63c045e6dcdcf19321a9908c303a32918a
Pointer size: 131 Bytes
Size of remote file: 417 kB

assets/SNEX-V1_benchmarks_small.png DELETED Viewed

Git LFS Details

SHA256: 6c0c25b58a6c2e95fcddf73d93481bbe4e008e291c7f5fda974e0722358216f7
Pointer size: 131 Bytes
Size of remote file: 331 kB