Instructions to use mlabonne/AlphaMonarch-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mlabonne/AlphaMonarch-7B with Transformers:

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

pipe = pipeline("text-generation", model="mlabonne/AlphaMonarch-7B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("mlabonne/AlphaMonarch-7B")
model = AutoModelForCausalLM.from_pretrained("mlabonne/AlphaMonarch-7B")
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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use mlabonne/AlphaMonarch-7B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mlabonne/AlphaMonarch-7B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mlabonne/AlphaMonarch-7B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/mlabonne/AlphaMonarch-7B

SGLang

How to use mlabonne/AlphaMonarch-7B 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 "mlabonne/AlphaMonarch-7B" \
    --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": "mlabonne/AlphaMonarch-7B",
		"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 "mlabonne/AlphaMonarch-7B" \
        --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": "mlabonne/AlphaMonarch-7B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use mlabonne/AlphaMonarch-7B with Docker Model Runner:
```
docker model run hf.co/mlabonne/AlphaMonarch-7B
```

Randomly switches to Russian and even inserts gibberish english on Q6_K on KoboldCPP + Silly Tavern. Mistral Instruct prompt format.

by balukumar - opened Mar 2, 2024

Discussion

balukumar

Mar 2, 2024

•

edited Mar 2, 2024

EDIT: This is still happening even on the Q8_0 quant.

I am asking it simple questions as an assistant. For example, I ask it who is the best mixed martial artist of all time and it starts decently well, but somewhere along the way, it starts answering in Russian and then turns into complete gibberish.

Also the times it does respond appropriately ( to other questions), it is extremely ( and unnecessarily ) verbose. It beats around the bush a lot with unnecessarily complex sounding vocabulary, but it's like its being vague just for the sake of it.

I am using the Mistral Instruct prompt format.

mlabonne

Owner Mar 4, 2024

Ah, I noticed it once with an extremely specific instruction. It might be some weird trigger word that switches it to Russian/gibberish. Would you mind sharing your instruction?

balukumar

Mar 5, 2024

I had asked it 'Who is the best mixed martial artist?' and I think it started switching to Russian after mentioning Khabib Nurmagomedov ( who is Russian )

mlabonne

Owner Mar 5, 2024

Is it something that happened once or does it happen every time you ask this question? I couldn't reproduce it in 10+ attempts.

balukumar

Mar 5, 2024

•

edited Mar 5, 2024

This kind of gibberish / Russian shows up on my end often.

Yet again

mlabonne

Owner Mar 6, 2024

•

edited Mar 6, 2024

Ok cool it looks like it can be solved by tweaking the inference parameters. Here's what LM Studio uses:

seyf1elislam

Mar 6, 2024

@siddhesh22 i saw this in some models when the min p is too low , just increase the min p set it to 0.05 or 0.1~ it will be solved .

balukumar

Mar 7, 2024

Ok cool it looks like it can be solved by tweaking the inference parameters. Here's what LM Studio uses:

Thank you! It's working really well now. Sillytavern has a 'neutralize samplers' setting which I was using previously which was causing the issue ( but it worked fine with other models) and after adjusting the values, I am getting much better results, the model is amazing!

mlabonne

Owner Mar 7, 2024

Thanks, glad it solved this problem! :)

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