roberta-base亲测好用 内心**深处上传283.71MB文件格式zipbert roberta-base是bert的加强版 (0)踩踩(0) 所需:1积分 大鱼吃小鱼.py 2025-01-24 21:23:40 积分:1 Egg traps.py 2025-01-24 20:52:02 积分:1 删除顺序表中指定值的所有元素.md
使用“BERT”作为编码器和解码器(BERT2BERT)来改进Seq2Seq文本摘要模型
datasets : squad_v2 license : cc-by-4.0 model_specific_defaults : ordereddict({'apply_deepspeed': 'true', 'apply_lora': 'true', 'apply_ort': 'true'}) SharedComputeCapacityEnabled task : question-answering hiddenlayerscanned huggingface_model_id : deepset/roberta-base-squad2 inference_compute...
roberta-baseroberta-base 喜爱 2 roberta-base pytorch_transformers 小 小风峰123 1枚 CC0 3 13 2020-04-27 详情 相关项目 评论(0) 创建项目 数据集介绍 roberta-base pytorch_transformers 文件列表 roberta-base.zip roberta-base.zip (283.71M) 下载 File Name Size Update Time roberta-base/config.json...
掌握 BERT：自然语言处理 (NLP) 从初级到高级的综合指南（2）
中国RoBERTa-wwm-base模型下载和使用指南 在自然语言处理(Natural Language Processing,NLP)领域,RoBERTa-wwm-base是一个非常流行的预训练模型。它是基于谷歌的BERT模型(Bidirectional Encoder Representations from Transformers)改进而来的,通过大规模的无监督学习从大量的文本数据中学习语言的上下文相关性。它可以用于多种NLP...
Specifically, this model is anxlm-roberta-basemodel that was fine-tuned on theIgbocorpus. document=DocumentAssembler()\.setInputCol("text")\.setOutputCol("document")sentencerDL=SentenceDetectorDLModel.pretrained("sentence_detector_dl","xx")\.setInputCols(["document"])\.setOutputCol("sentence"...
Compatibility:Spark NLP 3.1.0+ License:Open Source Edition:Official Input Labels:[token, sentence] Output Labels:[embeddings] Language:en Case sensitive:true Data Source https://huggingface.co/distilroberta-base Benchmarking When fine-tuned on downstream tasks, this model achieves the following result...
sent_xlm_roberta_base_finetuned_wolofis aWolof RoBERTamodel obtained by fine-tuningxlm-roberta-basemodel on Wolof language texts. It providesbetter performancethan the XLM-RoBERTa on named entity recognition datasets. Specifically, this model is anxlm-roberta-basemodel that was fine-tuned on theWo...
('sentence-transformers/stsb-distilroberta-base-v2') model = AutoModel.from_pretrained('sentence-transformers/stsb-distilroberta-base-v2') # Tokenize sentences encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt') # Compute token embeddings with torch.no_grad(...