Training models with ternary quantized weights using PyTorch
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Jun 12, 2019 - Python
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ternary-quantization
Here are 10 public repositories matching this topic...
n0x CLI is my go-to Claude Code alternative when I’m on a budget.
nodejs cli open-source npm typescript terminal ai developer-tools code-generation quantization bonsai low-resource ternary-quantization llm llama-cpp local-llm ollama react-agent offline-ai coding-agent
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Jul 4, 2026 - TypeScript
Pre-quantized ternary models for VLMs, multimodal, and audio — the models GGUF can't touch
quantization whisper gemma vlm model-compression multimodal edge-ai ternary-quantization huggingface apple-silicon vision-language-model qwen
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Apr 27, 2026 - Python
1.58-bit ternary Mamba LLM for Indian languages. Weights are {-1,0,+1} — inference uses only add/sub. 3B model fits in 750MB, runs 20+ tok/s on mobile.
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Apr 10, 2026 - Python
Selective ternary compression of Qwen3.6 MoE expert projections on Apple Silicon, with matched-control functional, routing, and perplexity evaluation.
machine-learning quantization mlx model-compression mixture-of-experts ternary-quantization apple-silicon large-language-models local-llm qwen
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Jul 31, 2026 - TypeScript
Research implementation of activation-aware ternary and mixed-bit quantization for Qwen3.8-27B, targeting 7-9 GB text inference on 16 GB GPUs.
transformers pytorch quantization model-compression mixed-precision ternary-quantization large-language-models llama-cpp gguf qwen3
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Aug 17, 2026 - Python
Colab-friendly BitNet distillation engine: collect KD traces from a teacher, train a ternary Mini-BitNet, and dry-run 7B memory. Multi-provider + Drive/S3
transformers pytorch parquet knowledge-distillation model-compression bitnet colab-notebook mixed-precision ternary-quantization large-language-model efficient-llm efficient-llm-inference activation-quantization kd-traces
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Sep 5, 2025 - Python
Anonymous paper release for TRACE-Q, a topology-aware ternary quantization framework for heterogeneous language models.
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Jul 30, 2026
PILON (Primitive-Induced Linear Operator Network) explores a compositional weight parameterization for transformer FFN layers. The goal is to replace dense FFN matrices with shared low-rank primitives plus learned composition weights.
research pytorch transformer language-model model-compression bitnet weight-sharing low-rank ternary-quantization quantization-aware-training efficient-deep-learning consumer-gpu
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Mar 20, 2026 - Python
Apple Silicon MLX low-bit ternary (BitNet b1.58 {-1,0,+1}) quantization, Metal GPU kernels, perplexity benchmarking, the cogito corpus pipeline
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Aug 25, 2026 - C++
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