Instructions to use FoxEngineAi/Mega-Destroyer-8x7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use FoxEngineAi/Mega-Destroyer-8x7B with Transformers:

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

pipe = pipeline("text-generation", model="FoxEngineAi/Mega-Destroyer-8x7B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("FoxEngineAi/Mega-Destroyer-8x7B")
model = AutoModelForCausalLM.from_pretrained("FoxEngineAi/Mega-Destroyer-8x7B")
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 FoxEngineAi/Mega-Destroyer-8x7B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "FoxEngineAi/Mega-Destroyer-8x7B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FoxEngineAi/Mega-Destroyer-8x7B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/FoxEngineAi/Mega-Destroyer-8x7B

SGLang

How to use FoxEngineAi/Mega-Destroyer-8x7B 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 "FoxEngineAi/Mega-Destroyer-8x7B" \
    --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": "FoxEngineAi/Mega-Destroyer-8x7B",
		"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 "FoxEngineAi/Mega-Destroyer-8x7B" \
        --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": "FoxEngineAi/Mega-Destroyer-8x7B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use FoxEngineAi/Mega-Destroyer-8x7B with Docker Model Runner:
```
docker model run hf.co/FoxEngineAi/Mega-Destroyer-8x7B
```

Is this meant to be used with alpaca prompt templates?

by left1000 - opened Mar 14, 2024

Discussion

left1000

Mar 14, 2024

Anyone have some specific recommendations for context template instruct template or text completion sampler presets for this model?

MrDragonFox

FoxEngineAi org Mar 14, 2024

i assume since its a mixtral merge - it shoud work with mixtral instruct and alpaca instruct

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