Instructions to use QuantaSparkLabs/Quantum-X with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use QuantaSparkLabs/Quantum-X with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("QuantaSparkLabs/Quantum-X")
model = AutoModelForCausalLM.from_pretrained("QuantaSparkLabs/Quantum-X")
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

vLLM

How to use QuantaSparkLabs/Quantum-X with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/QuantaSparkLabs/Quantum-X

SGLang

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

Docker Model Runner
How to use QuantaSparkLabs/Quantum-X with Docker Model Runner:
```
docker model run hf.co/QuantaSparkLabs/Quantum-X
```

QuantaSparkLabs commited on 10 days ago

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Update README.md

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@@ -13,6 +13,29 @@ tags:
 pipeline_tag: text-generation
 base_model: Qwen/Qwen2.5-0.5B-Instruct
 ---
 # Quantum-X

 pipeline_tag: text-generation
 base_model: Qwen/Qwen2.5-0.5B-Instruct
 ---
+<p align="center">
+  <img src="https://huggingface.co/QuantaSparkLabs/NYXIS-Pro/resolve/main/preview imgagee.png"
+       alt="NYXIS Logo"
+       width="160"
+       height="160"
+       style="border-radius: 50%; object-fit: cover;">
+</p>
+<p align="center">
+  <img src="https://huggingface.co/QuantaSparkLabs/NYXIS-Pro/resolve/main/logoname.png"
+       alt="NYXIS Name"
+       width="700"
+       style="border-radius: 18px;">
+</p>
+<p align="center">
+  <a href="https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct"><img src="https://img.shields.io/badge/Base-Qwen%202.5%200.5B-blueviolet" alt="Base Model"></a>
+  <a href="https://huggingface.co/datasets/teknium/OpenHermes-2.5"><img src="https://img.shields.io/badge/Data-OpenHermes%202.5-00BFFF" alt="Training Data"></a>
+  <a href="#"><img src="https://img.shields.io/badge/Fine--Tune-QLoRA%20%2B%20Unsloth-FF6F00" alt="Fine-Tune Method"></a>
+  <a href="#"><img src="https://img.shields.io/badge/Size-0.5B%20Params-lightgrey" alt="Model Size"></a>
+  <a href="#"><img src="https://img.shields.io/badge/Speed-Blazing%20Fast-brightgreen" alt="Speed"></a>
+  <a href="https://www.apache.org/licenses/LICENSE-2.0"><img src="https://img.shields.io/badge/License-Apache%202.0-yellow" alt="License"></a>
+</p>
 # Quantum-X