百亿参数的中英文双语基座大模型
Les fonctionnalités principales de openbmb/cpm-bee sont : Foundation Models, Text LLM Models.
Les alternatives open-source à openbmb/cpm-bee incluent : baichuan-inc/baichuan2 — Baichuan2 is a collection of pre-trained large language models, including base and chat variants, designed for natural… flagai-open/flagai — FlagAI is a distributed deep learning framework and platform designed for the end-to-end lifecycle of large-scale… 01-ai/yi — Yi is a bilingual language model and foundation model designed for natural language processing, reasoning, and reading… baichuan-inc/baichuan-7b — Baichuan-7B is an open-source 7 billion parameter bilingual Transformer model designed for text generation and… baichuan-inc/baichuan-13b — A 13B large language model developed by Baichuan Intelligent Technology. hit-scir/huozi — 活字通用大模型.
A 13B large language model developed by Baichuan Intelligent Technology
Baichuan-7B is an open-source 7 billion parameter bilingual Transformer model designed for text generation and few-shot learning across Chinese and English. It is built on a large Transformer architecture trained on a bilingual corpus, enabling it to produce coherent text in both languages from a single model. The model incorporates several optimization techniques that distinguish it from standard large language models. It uses rotary position embeddings that can extrapolate to longer sequences than seen during training, allowing context extension beyond the original 4096-token training lengt
Yi is a bilingual language model and foundation model designed for natural language processing, reasoning, and reading comprehension in both English and Chinese. It is built as a transformer-based architecture capable of general purpose text generation and conversational tasks. The model is distinguished by its ability to function as a long context system, processing and analyzing extended input sequences up to 200k tokens. It also supports quantized versions that use low-bit precision to reduce memory footprints, enabling execution on consumer-grade hardware. The project covers a broad rang
Baichuan2 is a collection of pre-trained large language models, including base and chat variants, designed for natural language generation and multi-turn conversational AI. It provides an inference engine and a fine-tuning framework to adapt these models to custom datasets and specialized domains. The project features a quantization toolkit and an inference engine that enable model execution across diverse hardware, including graphics processors, central processors, and specialized accelerators. These tools support low-bit weight quantization to reduce memory usage and increase inference spee