Instructions to use mlabonne/Beyonder-4x7B-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mlabonne/Beyonder-4x7B-v2 with Transformers:

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

pipe = pipeline("text-generation", model="mlabonne/Beyonder-4x7B-v2")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("mlabonne/Beyonder-4x7B-v2")
model = AutoModelForCausalLM.from_pretrained("mlabonne/Beyonder-4x7B-v2", device_map="auto")
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 Settings

vLLM

How to use mlabonne/Beyonder-4x7B-v2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mlabonne/Beyonder-4x7B-v2"
# 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/Beyonder-4x7B-v2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/mlabonne/Beyonder-4x7B-v2

SGLang

How to use mlabonne/Beyonder-4x7B-v2 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/Beyonder-4x7B-v2" \
    --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/Beyonder-4x7B-v2",
		"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/Beyonder-4x7B-v2" \
        --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/Beyonder-4x7B-v2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use mlabonne/Beyonder-4x7B-v2 with Docker Model Runner:
```
docker model run hf.co/mlabonne/Beyonder-4x7B-v2
```

mlabonne commited on Jan 5, 2024

Commit

a003286

1 Parent(s): fbd1559

Update README.md

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@@ -20,9 +20,11 @@ This model is a Mixure of Experts (MoE) made with [mergekit](https://github.com/
 |                               Model                                |AGIEval|GPT4All|TruthfulQA|Bigbench|Average|
 |--------------------------------------------------------------------|------:|------:|---------:|-------:|------:|
-|[Beyonder-4x7B-v2](https://huggingface.co/shadowml/Beyonder-4x7B-v2)|  45.29|  75.95|     60.86|    46.4|  57.13|
 |[NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B)|  43.67|  73.24|     55.37|   41.76|  53.51|
 |[OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B)|  42.75|  72.99|     52.99|   40.94|  52.42|
 ### AGIEval
 |             Task             |Version| Metric |Value|   |Stderr|

 |                               Model                                |AGIEval|GPT4All|TruthfulQA|Bigbench|Average|
 |--------------------------------------------------------------------|------:|------:|---------:|-------:|------:|
+|[**Beyonder-4x7B-v2**](https://huggingface.co/shadowml/Beyonder-4x7B-v2)|  **45.29**|  **75.95**|     <u>**60.86**</u>|    **46.4**|  **57.13**|
 |[NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B)|  43.67|  73.24|     55.37|   41.76|  53.51|
 |[OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B)|  42.75|  72.99|     52.99|   40.94|  52.42|
+|[Nous-Hermes-2-SOLAR-10.7B](https://huggingface.co/NousResearch/Nous-Hermes-2-SOLAR-10.7B)|  47.79|  74.69|     55.92|   44.84|  55.81|
+|[Nous-Hermes-2-Yi-34B](https://huggingface.co/NousResearch/Nous-Hermes-2-SOLAR-10.7B)|  <u>50.27</u>|  <u>76.00</u>|     60.34|   <u>46.69</u>|  <u>58.33</u>|
 ### AGIEval
 |             Task             |Version| Metric |Value|   |Stderr|