Instructions to use NTQAI/Nxcode-CQ-7B-orpo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use NTQAI/Nxcode-CQ-7B-orpo with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("NTQAI/Nxcode-CQ-7B-orpo")
model = AutoModelForCausalLM.from_pretrained("NTQAI/Nxcode-CQ-7B-orpo")
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 NTQAI/Nxcode-CQ-7B-orpo with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/NTQAI/Nxcode-CQ-7B-orpo

SGLang

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

Docker Model Runner
How to use NTQAI/Nxcode-CQ-7B-orpo with Docker Model Runner:
```
docker model run hf.co/NTQAI/Nxcode-CQ-7B-orpo
```

LLm Studio and Ollama not working for gguf

by Ekolawole - opened May 13, 2024

Discussion

Ekolawole

May 13, 2024

The GGUF alternatives of this models are not working on Ollama and llm Studio. Could it be the template or what is going on with the GGUF here?

Monor

May 13, 2024

The GGUF alternatives of this models are not working on Ollama and llm Studio. Could it be the template or what is going on with the GGUF here?

@Ekolawole thx, I have updated all the files, please use the latest version.

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