This model is a GGUF quantized version of Baidu's ERNIE-4.5-21B-A3B-Thinking model, using the Q8_0 quantization format and converted through the llama.cpp tool. It supports use in inference frameworks compatible with the GGUF format.

Natural Language ProcessingTransformersMultiple Languages

This is the MLX format conversion version of Baidu's ERNIE-4.5-21B-A3B-Thinking model, converted using the mlx-lm 0.27.1 tool and optimized for Apple Silicon devices, supporting efficient inference.

Natural Language ProcessingMlxMultiple Languages

A community version based on the Baidu ERNIE-4.5-21B-A3B model, implementing 8-bit quantization optimization using MLX, specifically optimized for Apple chip devices to improve performance and suitable for text generation tasks.

Natural Language ProcessingTransformersMultiple Languages

Baidu ERNIE-4.5-21B-A3B is a community version based on the ERNIE-4.5-21B-A3B-PT base model. It uses MLX for 6-bit quantization and is specifically optimized for Apple chips. This model is presented in the LM Studio Community Model Highlights Program and has efficient inference performance and good compatibility.

Natural Language ProcessingTransformersMultiple Languages

ERNIE-4.5-21B-A3B is a large language model developed by Baidu. It has been optimized with 4-bit quantization by the LM Studio team using the MLX framework, specifically optimized for Apple chips. This model has 21 billion parameters, supports Chinese and English, and uses the Apache-2.0 open-source license.

Natural Language ProcessingTransformersMultiple Languages

ERNIE-4.5-21B-A3B-PT-8bit is an 8-bit quantized version of Baidu's ERNIE-4.5-21B-A3B-PT model, converted to MLX format and suitable for Apple Silicon devices.

Natural Language ProcessingMlxMultiple Languages

ERNIE-4.5-0.3B-PT-bf16 is a version of the ERNIE series models developed by Baidu, with a parameter scale of 0.3B and trained using bf16 precision.

Natural Language ProcessingMlxMultiple Languages

A quantized version of the Baidu ERNIE-4.5-21B-A3B-PT model, quantized through llama.cpp to improve the operating efficiency and performance in different hardware environments.

Natural Language ProcessingGguf

A quantized version based on the Baidu ERNIE-4.5-0.3B-PT model, optimized through the llama.cpp tool to reduce the model size and improve the running efficiency.

Natural Language ProcessingGgufMultiple Languages

Baidu ERNIE 4.5 0.3B is a bilingual text generation model based on the Transformer architecture, which performs excellently in general language understanding and generation tasks. It supports Chinese-English bilingual processing, and the context length can reach 128k tokens.

Natural Language ProcessingGgufMultiple Languages

This model is a GGUF format conversion version of Baidu's ERNIE-4.5-0.3B-PT, supporting Chinese and English text generation tasks.

Natural Language ProcessingGgufMultiple Languages

ERNIE-Code is a unified large language model connecting 116 natural languages and 6 programming languages, supporting various cross-lingual tasks.

Natural Language ProcessingTransformers

This is a multilingual model supporting 100 languages, specifically designed for natural language inference (NLI) and zero-shot classification tasks. It is based on the Baidu ERNIE-M architecture and fine-tuned on the XNLI and MNLI datasets.

Natural Language ProcessingTransformersMultiple Languages

ERNIE 3.0 is a large-scale knowledge-enhanced pre-trained model for language understanding and generation, developed by Baidu.

Natural Language ProcessingTransformersChinese

ERNIE 3.0 is a large-scale knowledge-enhanced pre-training model launched by Baidu for language understanding and generation, with micro-zh being its small Chinese version.

Natural Language ProcessingTransformersChinese

ERNIE 3.0 is a large-scale knowledge-enhanced pre-trained model for language understanding and generation, developed by Baidu.

Natural Language ProcessingTransformersChinese

ERNIE 3.0 is a large-scale knowledge-enhanced pre-trained model for Chinese language understanding and generation, developed by Baidu Research.

Natural Language ProcessingTransformersChinese

SKEP (Sentiment Knowledge Enhanced Pre-training) was proposed by Baidu in 2020, specifically designed for sentiment analysis tasks. The model incorporates multi-type knowledge through sentiment masking techniques and three sentiment pre-training objectives.

Natural Language ProcessingTransformersEnglish

A BERT model based on bert-base-chinese, trained and optimized on the Baidu Knows question matching dataset, suitable for open-domain question matching scenarios.

Natural Language ProcessingTransformers

A pre-trained Albert large-scale Chinese Q&A model based on Baidu WebQA and Baidu DuReader datasets, suitable for Chinese Q&A tasks.

Natural Language ProcessingTransformersChinese