Instructions to use inclusionAI/GroveMoE-Inst with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use inclusionAI/GroveMoE-Inst with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="inclusionAI/GroveMoE-Inst", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("inclusionAI/GroveMoE-Inst", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("inclusionAI/GroveMoE-Inst", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use inclusionAI/GroveMoE-Inst with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/inclusionAI/GroveMoE-Inst

SGLang

How to use inclusionAI/GroveMoE-Inst with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "inclusionAI/GroveMoE-Inst" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "inclusionAI/GroveMoE-Inst",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "inclusionAI/GroveMoE-Inst" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "inclusionAI/GroveMoE-Inst",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use inclusionAI/GroveMoE-Inst with Docker Model Runner:
```
docker model run hf.co/inclusionAI/GroveMoE-Inst
```

llama.cpp support

by djuna - opened Aug 20, 2025

Discussion

djuna

Aug 20, 2025

Will you add this model architecture into llama.cpp?

CISCai

Aug 22, 2025

See ggml-org/llama.cpp#15510.

MrDevolver

Sep 14, 2025

See ggml-org/llama.cpp#15510.

I see this still has not been merged. Is this adding full support and merge ready? What's taking so long?

CISCai

Sep 15, 2025

I see this still has not been merged. Is this adding full support and merge ready? What's taking so long?

It was a draft for a while pending a necessary GGML feature, it is now just pending review. In the mean time, if you can, please build it yourself and test, it is fully functional.

smcleod

Sep 25, 2025

Looks like it's been merged now FYI

djuna

Sep 26, 2025

Nice. Thanks lcpp team.

djuna changed discussion status to closed Sep 26, 2025

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment