AWQ quantization: done by stelterlab in INT4 GEMM with AutoAWQ by casper-hansen (https://github.com/casper-hansen/AutoAWQ/) Original Weights by Qwen AI/Finetuned by Microsoft. Original Model Card follows: > NextCoder: Robust Adaptation of Code LMs to Diverse Code Edits (ICML’2025) NextCoder is the latest series of Code-Editing large language models developed using the Qwen2.5-Coder Instruct variants as base and trained with novel Selective Knowledge Transfer finetuning methodology as introduced in the paper. NextCoder family model comes in 3 different sizes 7, 14, 32 billion parameters, to meet the needs of different developers. Following are the key improvements: — Significantly improvements in code editing, NextCoder-32B has performing on par with GPT-4o on complex benchmarks like Aider-Polyglot with performance increment of 44% from their base model. — No loss of generalizibility, due to our new finetuning method SeleKT — Long-context Support up to 32K tokens. This repo contains the NextCoder-32B model, which has the following features: — Type: Causal Language Models — Training Stage: Post-training with SeleKT — Architecture: transformers with RoPE, SwiGLU, RMSNorm, and…
Модальности:
Генерация текста
Области применения:
Генерация кода Диалог / чат
Задача: Генерация текста
Автор: stelterlab
Теги: qwen2, code, chat, microsoft, nextcoder, selekt, conversational, en
Лайков: 4 | Загрузок: 77
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
