Auramind-180M - 180M Parameters

Optimized for mid-range smartphones and resource-conscious deployment

Specifications

• Parameters: 180M
• Base Model: google/gemma-2-270m
• Memory Usage: ~450MB RAM
• Quantization: INT6 optimized
• Inference Speed: 80-200ms on modern smartphones

Mobile Deployment

This variant is specifically optimized for:

• Target Devices: Mid-range smartphones
• Memory Requirements: ~450MB RAM
• Performance: 80-200ms on modern smartphones

Usage

from transformers import AutoTokenizer, AutoModelForCausalLM

# Load this specific variant
tokenizer = AutoTokenizer.from_pretrained("zail-ai/auramind-180m")
model = AutoModelForCausalLM.from_pretrained(
    "zail-ai/auramind-180m",
    torch_dtype=torch.float16,
    device_map="auto",
    low_cpu_mem_usage=True
)

Refer to the main AuraMind repository for complete documentation.