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from __future__ import annotations
from transformers import PretrainedConfig
from transformers import PreTrainedModel
from torch import nn
import torch
class FastTextJpConfig(PretrainedConfig):
model_type = "fasttext_jp"
def __init__(self, **kwargs):
super().__init__(**kwargs)
class FastTextJpModel(PreTrainedModel):
"""FastTextのEmbeddingを行います。
"""
config_class = FastTextJpConfig
def __init__(self, config: FastTextJpConfig):
super().__init__(config)
self.word_embeddings = nn.Embedding(config.vocab_size,
config.hidden_size)
def forward(self, input_ids, **kwargs):
return self.word_embeddings(torch.tensor([0]))
FastTextJpConfig.register_for_auto_class()
FastTextJpModel.register_for_auto_class("AutoModel")
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