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# coding=utf-8
# Copyright 2022 x-plug and The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Tokenization classes for MplugOwl."""
from transformers.utils import logging
from transformers.models.llama.tokenization_llama import LlamaTokenizer
logger = logging.get_logger(__name__)
VOCAB_FILES_NAMES = {"vocab_file": "vocab.txt"}
PRETRAINED_VOCAB_FILES_MAP = {
"vocab_file": {
"MAGAer13/mplug-owl-llama-7b": "https://huggingface.co/MAGAer13/mplug-owl-llama-7b/resolve/main/vocab.txt",
},
}
PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES = {
"MAGAer13/mplug-owl-llama-7b": 2048,
}
class MplugOwlTokenizer(LlamaTokenizer):
def __init__(
self,
vocab_file,
unk_token="<unk>",
bos_token="<s>",
eos_token="</s>",
pad_token="<unk>",
sp_model_kwargs=None,
add_bos_token=False,
add_eos_token=False,
clean_up_tokenization_spaces=False,
**kwargs,
):
super().__init__(
vocab_file,
unk_token,
bos_token,
eos_token,
pad_token,
sp_model_kwargs,
add_bos_token,
add_eos_token,
clean_up_tokenization_spaces,
**kwargs,
)
self.eod_id = self.eos_token_id
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