QTensor Asymmetric 2.0 (Hybrid Bridge)
This model is a highly compressed version of TinyLlama-1.1B-Chat-v1.0, utilizing the QTensor Asymmetric 2.0 framework. It achieves massive VRAM reductions by applying mathematically distinct compression topologies to different architectural components, maintaining zero-shot performance and fluency.
Architecture
- Attention Layers (The Eyes): Compressed via Block-SVD (r=16) + 3.0% SpLoRA.
- MLP Layers (The Muscle): Compressed via Channel-Wise INT4 + LoRA.
- Harmonization: Employs a 1D Rank-1 Subspace Bridge (
subspace_bridge) to harmonize variance mismatches between the SVD residual stream and INT4 inputs.
Performance & Footprint
- VRAM Footprint: ~1.16 GB
- HellaSwag (Zero-Shot): 38.0%
- WikiText-2 (Zero-Shot Perplexity): 168.46
Usage
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "your-username/qtensor-tinyllama-hybrid-v2"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
trust_remote_code=True,
torch_dtype=torch.bfloat16
)
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