Instructions to use maxcurrent/NeuralMonarchCoderPearlBeagle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use maxcurrent/NeuralMonarchCoderPearlBeagle with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("maxcurrent/NeuralMonarchCoderPearlBeagle")
model = AutoModelForCausalLM.from_pretrained("maxcurrent/NeuralMonarchCoderPearlBeagle")
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 maxcurrent/NeuralMonarchCoderPearlBeagle with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/maxcurrent/NeuralMonarchCoderPearlBeagle

SGLang

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

Docker Model Runner
How to use maxcurrent/NeuralMonarchCoderPearlBeagle with Docker Model Runner:
```
docker model run hf.co/maxcurrent/NeuralMonarchCoderPearlBeagle
```

Max Current commited on Mar 26, 2024

Commit

59cb1e3

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1 Parent(s): 47df4bb

Update README.md

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@@ -129,7 +129,9 @@ This is a TIES merge, formed from MonarchCoder-7b (A merge of Alpha Monarch and
 It is a somewhat haphazard experiment to see if we can merge more math and coding capabilities into the already outstanding NeuralBeagle14-7b and still maintain the same positive chat abilities.
 If you find this or my other merges useful, please consider sending a bit of BTC so I don't have to use Google Colab :D
 BTC: bc1q8lc4mzdtdyz7fx44vaw3jn8qg6w4c3ypfxpdrv
 ETH/POLYGON: 0x102a6fd187db8441d2cbead33ac70e87f382f114
 ## 🧩 Configuration

 It is a somewhat haphazard experiment to see if we can merge more math and coding capabilities into the already outstanding NeuralBeagle14-7b and still maintain the same positive chat abilities.
 If you find this or my other merges useful, please consider sending a bit of BTC so I don't have to use Google Colab :D
 BTC: bc1q8lc4mzdtdyz7fx44vaw3jn8qg6w4c3ypfxpdrv
 ETH/POLYGON: 0x102a6fd187db8441d2cbead33ac70e87f382f114
 ## 🧩 Configuration