Instructions to use anthracite-org/magnum-v1-72b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use anthracite-org/magnum-v1-72b with Transformers:

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

pipe = pipeline("text-generation", model="anthracite-org/magnum-v1-72b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("anthracite-org/magnum-v1-72b")
model = AutoModelForCausalLM.from_pretrained("anthracite-org/magnum-v1-72b", 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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use anthracite-org/magnum-v1-72b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "anthracite-org/magnum-v1-72b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "anthracite-org/magnum-v1-72b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/anthracite-org/magnum-v1-72b

SGLang

How to use anthracite-org/magnum-v1-72b 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 "anthracite-org/magnum-v1-72b" \
    --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": "anthracite-org/magnum-v1-72b",
		"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 "anthracite-org/magnum-v1-72b" \
        --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": "anthracite-org/magnum-v1-72b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use anthracite-org/magnum-v1-72b with Docker Model Runner:
```
docker model run hf.co/anthracite-org/magnum-v1-72b
```

Samplers

by opendev - opened Jun 20, 2024

Discussion

opendev

Jun 20, 2024

Nice model.
What is Text completion presets?
Instruct template?

For context it uses ChatML.

alpindale

Jun 20, 2024

ChatML instruct.

For sampler, I recommend temperature and min_p only. Temp around 1-1.1. Min_p around 0.06-0.07

Adzeiros

Jun 23, 2024

I cannot find settings where the responses aren't nonsense. It seems random, like for a good chunk it's fine responses and then just randomly it will start speaking as if it doesn't speak English and is trying to guess how to talk.

Ainonake

Jun 23, 2024

I cannot find settings where the responses aren't nonsense. It seems random, like for a good chunk it's fine responses and then just randomly it will start speaking as if it doesn't speak English and is trying to guess how to talk.

Are you using gguf q4km?

JoggyMuffin

Jul 21, 2024

I cannot find settings where the responses aren't nonsense. It seems random, like for a good chunk it's fine responses and then just randomly it will start speaking as if it doesn't speak English and is trying to guess how to talk.

There is a bug with CuBLAS and Qwen2, which this model is based on. I recommend giving a different prompt processing backend like Vulkan a try and seeing if that fixes it

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