W8A8 (8-bit weights and activations) quantized version of Qwen/Qwen3-Coder-30B-A3B-Instruct using LLM-Compressor. — 🗜️ Memory: ~50% reduction vs FP16 — 🚀 Speed: Faster inference on supported hardware — 🔗 Original model: https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct — 🏗️ Recommended architectures: Ampere and older Qwen3-Coder is available in multiple sizes. Today, we’re excited to introduce Qwen3-Coder-30B-A3B-Instruct. This streamlined model maintains impressive performance and efficiency, featuring the following key enhancements: — Significant Performance among open models on Agentic Coding, Agentic Browser-Use, and other foundational coding tasks. — Long-context Capabilities with native support for 256K tokens, extendable up to 1M tokens using Yarn, optimized for repository-scale understanding. — Agentic Coding supporting for most platform such as Qwen Code, CLINE, featuring a specially designed function call format. Qwen3-Coder-30B-A3B-Instruct has the following features: — Type: Causal Language Models — Training Stage: Pretraining & Post-training — Number of Parameters: 30.5B in total and 3.3B activated — Number of Layers: 48 — Number of Attention Heads (GQA): 32…
Модальности:
Генерация текста
Области применения:
Диалог / чат Генерация кода Следование инструкциям Математика
Задача: Генерация текста
Автор: ramblingpolymath
Теги: qwen3_moe, quantized, w8a8, llm-compressor, conversational, endpoints_compatible, 8-bit, compressed-tensors
Лайков: 3 | Загрузок: 683
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
