transformers.tokenization_utils_base.BatchEncoding 是Hugging Face 的 transformers 库中用于处理批量文本编码结果的一个核心类。下面是对其详细解答: 1. 基本功能 BatchEncoding 类主要用于封装 tokenizer 处理文本后生成的批量编码结果。这些编码结果通常包括输入 ID、注意力掩码、类型 ID 等,以便于后续的模型输入。 2...
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX. - transformers/src/transformers/tokenization_utils_base.py at v4.37.2 · huggingface/transformers
not None: 2533 self._switch_to_target_mode() File /home/ec2-user/anaconda3/envs/llm-gen/lib/python3.10/site-packages/transformers/tokenization_utils_base.py:2617, in PreTrainedTokenizerBase._call_one(self, text, text_pair, add_special_tokens, padding, truncation, max_length, stride, is_...
from transformers.tokenization_utils_base import EncodedInput, BatchEncoding from typing import Dict import sentencepiece as spm import numpy as np logger = logging.get_logger(__name__) PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES = { "THUDM/chatglm-6b": 2048, } class TextTokenizer: def...
tokenizer = BertWordPieceTokenizer("bert-base-uncased-vocab.txt", lowercase=True) The tokenization pipeline tokenizer在编码时的pipeline: normalization pre-tokenization model post-processing Normalization: 清理、删除空格、删除变音符号、小写化、Unicode normalization from tokenizers import normalizers from tokeniz...
from file_utils import cached_path logger = logging.getLogger(__name__) PRETRAINED_VOCAB_ARCHIVE_MAP = { 'bert-base-uncased': "https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-uncased-vocab.txt", 'bert-large-uncased': "https://s3.amazonaws.com/models.huggingface.co/bert...
Manticore provides built-in support for indexing languages with continuous scripts (i.e., languages that do not use spaces or other marks between words or sentences). This allows you to process texts in these languages in two different ways:...
In AutoTokenizer, it seems that TOKENIZER_MAPPING is used in this pattern, so I first intended to import AutoTokenizer in tokenization_utils_base.py, but it was a circular import. 😂 sgugger closed this as completed in #12619 Jul 17, 2021 Sign up for free to join this conversation on...
│ ers/tokenization_utils_base.py:2311 in _from_pretrained │ │ │ │ 2308 │ │ │ │ 2309 │ │ # Instantiate the tokenizer. │ │ 2310 │ │ try: │ │ ❱ 2311 │ │ │ tokenizer = cls(*init_inputs, **init_kwargs) │ ...
from .file_utils import cached_path logger = logging.getLogger(__name__) PRETRAINED_VOCAB_ARCHIVE_MAP = { 'bert-base-uncased': "https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-uncased-vocab.txt", 'bert-large-uncased': "https://s3.amazonaws.com/models.huggingface.co/...