Instructions to use IsValorum/Clover-35B-A3B-Preview-BF16-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 IsValorum/Clover-35B-A3B-Preview-BF16-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 IsValorum/Clover-35B-A3B-Preview-BF16-GGUF:BF16
# Run inference directly in the terminal:
llama cli -hf IsValorum/Clover-35B-A3B-Preview-BF16-GGUF:BF16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf IsValorum/Clover-35B-A3B-Preview-BF16-GGUF:BF16
# Run inference directly in the terminal:
llama cli -hf IsValorum/Clover-35B-A3B-Preview-BF16-GGUF: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 IsValorum/Clover-35B-A3B-Preview-BF16-GGUF:BF16
# Run inference directly in the terminal:
./build/bin/llama cli -hf IsValorum/Clover-35B-A3B-Preview-BF16-GGUF:BF16

Use Docker

docker model run hf.co/IsValorum/Clover-35B-A3B-Preview-BF16-GGUF:BF16

Llama new
LM Studio
Jan

vLLM

How to use IsValorum/Clover-35B-A3B-Preview-BF16-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "IsValorum/Clover-35B-A3B-Preview-BF16-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": "IsValorum/Clover-35B-A3B-Preview-BF16-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/IsValorum/Clover-35B-A3B-Preview-BF16-GGUF:BF16

Ollama
How to use IsValorum/Clover-35B-A3B-Preview-BF16-GGUF with Ollama:
```
ollama run hf.co/IsValorum/Clover-35B-A3B-Preview-BF16-GGUF:BF16
```
Unsloth Desktop

How to use IsValorum/Clover-35B-A3B-Preview-BF16-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf IsValorum/Clover-35B-A3B-Preview-BF16-GGUF: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": "IsValorum/Clover-35B-A3B-Preview-BF16-GGUF:BF16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use IsValorum/Clover-35B-A3B-Preview-BF16-GGUF with Docker Model Runner:
```
docker model run hf.co/IsValorum/Clover-35B-A3B-Preview-BF16-GGUF:BF16
```

Lemonade

How to use IsValorum/Clover-35B-A3B-Preview-BF16-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull IsValorum/Clover-35B-A3B-Preview-BF16-GGUF:BF16

Run and chat with the model

lemonade run user.Clover-35B-A3B-Preview-BF16-GGUF-BF16

List all available models

lemonade list

Hermes Agent

How to use IsValorum/Clover-35B-A3B-Preview-BF16-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 IsValorum/Clover-35B-A3B-Preview-BF16-GGUF: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 IsValorum/Clover-35B-A3B-Preview-BF16-GGUF:BF16

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use IsValorum/Clover-35B-A3B-Preview-BF16-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf IsValorum/Clover-35B-A3B-Preview-BF16-GGUF: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 "IsValorum/Clover-35B-A3B-Preview-BF16-GGUF: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"

Clover-35B-A3B-Preview BF16 GGUF

Clover quantization by IsValorum

Hugging Face | Ko-fi

BF16 GGUF of Diffuspace/Clover-35B-A3B-Preview at revision 4b0402b65e523d0183a14c431955438714cb16ff.

This file does not load in vanilla llama.cpp. Clover uses the clover_moe architecture, which upstream does not implement. Use the precompiled builds in IsValorum/llama.cpp-clover-moe, which ships Linux x86_64 CPU and CUDA 12 builds plus a Windows x86_64 universal package (NVIDIA CUDA 12.8, Vulkan for AMD and Intel GPUs, and CPU), or compile the runtime from the patched branch (PR #31306, commit 4838ffb0c8ade92f34d9157deea38d92758ab824). The CUDA builds need an NVIDIA GPU; the CPU builds run on any x86-64 machine.

The Linux x86_64 archives require GLIBC_2.38 or newer, so run them on Ubuntu 24.04 or equivalent; the Windows package has no glibc requirement.

What the prebuilt runtimes cover. Linux x86_64: any CPU, and NVIDIA CUDA 12 for sm_80/86/89/90. Windows x86_64, in a single universal package: NVIDIA CUDA 12.8 from sm_50 through sm_120, AMD and Intel GPUs through Vulkan 1.4.363, and any CPU with per-CPU backends. Not covered: macOS, ARM64, ROCm, and Blackwell on Linux; those need a build from the same branch and commit.

File	Size	SHA256
`Clover-35B-A3B-Preview-BF16.gguf`	69.38 GB (64.61 GiB)	`f6dca59b571d3a0ca070b36fa45ec8e1c233fdd01018fb5b86a5af246e32c78e`

export LD_LIBRARY_PATH=/path/to/llama-clover-bin:$LD_LIBRARY_PATH
llama-cli -m Clover-35B-A3B-Preview-BF16.gguf -ngl 99 -fa on -c 4096 -p "Hello"

Drop -ngl 99 on the CPU build.

A 1.25M I-Matrix will be published separately.

Downloads last month: 1,132

GGUF

Model size

35B params

Architecture

clover_moe

Hardware compatibility

16-bit

Model tree for IsValorum/Clover-35B-A3B-Preview-BF16-GGUF

Base model

Qwen/Qwen3.6-35B-A3B

Finetuned

Diffuspace/Clover-35B-A3B-Preview

Quantized

(16)

this model

Collection including IsValorum/Clover-35B-A3B-Preview-BF16-GGUF

Clover-35B-A3B Preview

Collection

Prebuilt llama.cpp runtime and GGUF files for Diffuspace/Clover-35B-A3B-Preview. • 4 items • Updated 5 days ago