How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "N-Bot-Int/ZoraBetaA2-Q16"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "N-Bot-Int/ZoraBetaA2-Q16",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Use Docker
docker model run hf.co/N-Bot-Int/ZoraBetaA2-Q16:F16
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GGUF Version

GGUF with Quants! Allowing you to run models using KoboldCPP and other AI Environments!

Quantizations:

Quant Type Benefits Cons
Q16_0 ✅ Highest accuracy (closest to full model) ❌ Requires significantly more VRAM/RAM
✅ Best for complex reasoning & detailed outputs ❌ Slower inference compared to Q4 & Q5
✅ Suitable for high-end GPUs & serious workloads ❌ Larger file size (takes more storage)

Model Details:

Read the Model details on huggingface Model Detail Here

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GGUF
Model size
7B params
Architecture
llama
Hardware compatibility
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16-bit

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