Sentence Transformer (句子转换器)
- SentenceTransformer (句子转换器)
- SentenceTransformer (句子转换器)
SentenceTransformer (句子转换器)SentenceTransformer.active_adapters() (激活的适配器)SentenceTransformer.add_adapter() (添加适配器)SentenceTransformer.bfloat16()SentenceTransformer.compile() (编译)SentenceTransformer.cpu()SentenceTransformer.cuda()SentenceTransformer.delete_adapter() (删除适配器)SentenceTransformer.device (设备)SentenceTransformer.disable_adapters() (禁用适配器)SentenceTransformer.double()SentenceTransformer.enable_adapters() (启用适配器)SentenceTransformer.encode() (编码)SentenceTransformer.encode_document() (编码文档)SentenceTransformer.encode_multi_process() (多进程编码)SentenceTransformer.encode_query() (编码查询)SentenceTransformer.eval() (评估)SentenceTransformer.evaluate() (评估)SentenceTransformer.fit() (拟合)SentenceTransformer.float()SentenceTransformer.get_adapter_state_dict() (获取适配器状态字典)SentenceTransformer.get_backend() (获取后端)SentenceTransformer.get_max_seq_length() (获取最大序列长度)SentenceTransformer.get_sentence_embedding_dimension() (获取句子嵌入维度)SentenceTransformer.half()SentenceTransformer.load_adapter() (加载适配器)SentenceTransformer.max_seq_length (最大序列长度)SentenceTransformer.model_card_data_class (模型卡数据类)SentenceTransformer.old_fit() (旧版拟合)SentenceTransformer.push_to_hub() (推送到Hub)SentenceTransformer.save_pretrained() (保存预训练模型)SentenceTransformer.set_adapter() (设置适配器)SentenceTransformer.set_pooling_include_prompt() (设置池化包含提示)SentenceTransformer.similarity (相似度)SentenceTransformer.similarity_fn_name (相似度函数名称)SentenceTransformer.similarity_pairwise (成对相似度)SentenceTransformer.smart_batching_collate() (智能批处理整理)SentenceTransformer.start_multi_process_pool() (启动多进程池)SentenceTransformer.stop_multi_process_pool() (停止多进程池)SentenceTransformer.to()SentenceTransformer.tokenize() (分词)SentenceTransformer.tokenizer (分词器)SentenceTransformer.train() (训练)SentenceTransformer.transformers_model (transformers模型)SentenceTransformer.truncate_sentence_embeddings() (截断句子嵌入)
- SentenceTransformerModelCardData (句子转换器模型卡数据)
- SimilarityFunction (相似度函数)
- SentenceTransformer (句子转换器)
- 训练器 (Trainer)
- SentenceTransformerTrainer (句子转换器训练器)
SentenceTransformerTrainer (句子转换器训练器)SentenceTransformerTrainer.add_callback() (添加回调)SentenceTransformerTrainer.add_dataset_name_transform() (添加数据集名称转换)SentenceTransformerTrainer.add_model_card_callback() (添加模型卡回调)SentenceTransformerTrainer.compute_loss() (计算损失)SentenceTransformerTrainer.create_model_card() (创建模型卡)SentenceTransformerTrainer.create_optimizer() (创建优化器)SentenceTransformerTrainer.create_optimizer_and_scheduler() (创建优化器和调度器)SentenceTransformerTrainer.create_scheduler() (创建调度器)SentenceTransformerTrainer.evaluate() (评估)SentenceTransformerTrainer.get_batch_sampler() (获取批采样器)SentenceTransformerTrainer.get_eval_dataloader() (获取评估数据加载器)SentenceTransformerTrainer.get_learning_rates() (获取学习率)SentenceTransformerTrainer.get_multi_dataset_batch_sampler() (获取多数据集批采样器)SentenceTransformerTrainer.get_num_trainable_parameters() (获取可训练参数数量)SentenceTransformerTrainer.get_optimizer_group() (获取优化器组)SentenceTransformerTrainer.get_test_dataloader() (获取测试数据加载器)SentenceTransformerTrainer.get_train_dataloader() (获取训练数据加载器)SentenceTransformerTrainer.hyperparameter_search() (超参数搜索)SentenceTransformerTrainer.is_local_process_zero() (是否为本地零号进程)SentenceTransformerTrainer.is_world_process_zero() (是否为全局零号进程)SentenceTransformerTrainer.log() (日志)SentenceTransformerTrainer.maybe_add_dataset_name_column() (可能添加数据集名称列)SentenceTransformerTrainer.pop_callback() (弹出回调)SentenceTransformerTrainer.preprocess_dataset() (预处理数据集)SentenceTransformerTrainer.propagate_args_to_deepspeed() (将参数传播到DeepSpeed)SentenceTransformerTrainer.push_to_hub() (推送到Hub)SentenceTransformerTrainer.remove_callback() (移除回调)SentenceTransformerTrainer.save_model() (保存模型)SentenceTransformerTrainer.set_initial_training_values() (设置初始训练值)SentenceTransformerTrainer.train() (训练)
- SentenceTransformerTrainer (句子转换器训练器)
- 训练参数
- SentenceTransformerTrainingArguments (句子转换器训练参数)
SentenceTransformerTrainingArguments (句子转换器训练参数)SentenceTransformerTrainingArguments.ddp_timeout_delta (DDP超时增量)SentenceTransformerTrainingArguments.device (设备)SentenceTransformerTrainingArguments.eval_batch_size (评估批大小)SentenceTransformerTrainingArguments.get_process_log_level() (获取进程日志级别)SentenceTransformerTrainingArguments.get_warmup_steps() (获取预热步数)SentenceTransformerTrainingArguments.local_process_index (本地进程索引)SentenceTransformerTrainingArguments.main_process_first() (主进程优先)SentenceTransformerTrainingArguments.n_gpu (GPU数量)SentenceTransformerTrainingArguments.parallel_mode (并行模式)SentenceTransformerTrainingArguments.place_model_on_device (将模型放置在设备上)SentenceTransformerTrainingArguments.process_index (进程索引)SentenceTransformerTrainingArguments.set_dataloader() (设置数据加载器)SentenceTransformerTrainingArguments.set_evaluate() (设置评估)SentenceTransformerTrainingArguments.set_logging() (设置日志记录)SentenceTransformerTrainingArguments.set_lr_scheduler() (设置学习率调度器)SentenceTransformerTrainingArguments.set_optimizer() (设置优化器)SentenceTransformerTrainingArguments.set_push_to_hub() (设置推送到Hub)SentenceTransformerTrainingArguments.set_save() (设置保存)SentenceTransformerTrainingArguments.set_testing() (设置测试)SentenceTransformerTrainingArguments.set_training() (设置训练)SentenceTransformerTrainingArguments.should_log (应记录日志)SentenceTransformerTrainingArguments.should_save (应保存)SentenceTransformerTrainingArguments.to_dict() (转换为字典)SentenceTransformerTrainingArguments.to_json_string() (转换为JSON字符串)SentenceTransformerTrainingArguments.to_sanitized_dict() (转换为净化字典)SentenceTransformerTrainingArguments.train_batch_size (训练批大小)SentenceTransformerTrainingArguments.world_size (全局大小)
- SentenceTransformerTrainingArguments (句子转换器训练参数)
- 损失函数
- BatchAllTripletLoss (批内所有三元组损失)
- BatchHardSoftMarginTripletLoss (批内难例软间隔三元组损失)
- BatchHardTripletLoss (批内难例三元组损失)
- BatchSemiHardTripletLoss (批内半难例三元组损失)
- ContrastiveLoss (对比损失)
- OnlineContrastiveLoss (在线对比损失)
- ContrastiveTensionLoss (对比张力损失)
- ContrastiveTensionLossInBatchNegatives (批内负例对比张力损失)
- CoSENTLoss
- AnglELoss
- CosineSimilarityLoss (余弦相似度损失)
- DenoisingAutoEncoderLoss (去噪自编码器损失)
- GISTEmbedLoss
- CachedGISTEmbedLoss (缓存GISTEmbed损失)
- MSELoss (均方误差损失)
- MarginMSELoss (间隔均方误差损失)
- MatryoshkaLoss (套娃损失)
- Matryoshka2dLoss (二维套娃损失)
- AdaptiveLayerLoss (自适应层损失)
- MegaBatchMarginLoss (大批量间隔损失)
- MultipleNegativesRankingLoss (多负例排序损失)
- CachedMultipleNegativesRankingLoss (缓存多负例排序损失)
- MultipleNegativesSymmetricRankingLoss (多负例对称排序损失)
- CachedMultipleNegativesSymmetricRankingLoss (缓存多负例对称排序损失)
- SoftmaxLoss (Softmax损失)
- TripletLoss (三元组损失)
- DistillKLDivLoss (蒸馏KL散度损失)
- 采样器
- 评估
- BinaryClassificationEvaluator (二元分类评估器)
- EmbeddingSimilarityEvaluator (嵌入相似度评估器)
- InformationRetrievalEvaluator (信息检索评估器)
- NanoBEIREvaluator
- MSEEvaluator (均方误差评估器)
- ParaphraseMiningEvaluator (转述挖掘评估器)
- RerankingEvaluator (重排序评估器)
- SentenceEvaluator (句子评估器)
- SequentialEvaluator (序列评估器)
- TranslationEvaluator (翻译评估器)
- TripletEvaluator (三元组评估器)
- 数据集
- 模块
- 主模块
- 更多模块
- 基础模块
Module (模块)Module.config_file_name (模块配置文件名)Module.config_keys (模块配置键)Module.forward() (前向传播)Module.get_config_dict() (获取配置字典)Module.load() (加载)Module.load_config() (加载配置)Module.load_dir_path() (加载目录路径)Module.load_file_path() (加载文件路径)Module.load_torch_weights() (加载Torch权重)Module.save() (保存)Module.save_config() (保存配置)Module.save_in_root (保存在根目录)Module.save_torch_weights() (保存Torch权重)
InputModule (输入模块)
- quantization (量化)