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README.md
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---
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license: mit
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---
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license: mit
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---
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# Disclamer
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I do not own, distribute, or take credits for this model, all copyrights belong to [Instadeep](https://huggingface.co/InstaDeepAI) under the [MIT licence](https://github.com/instadeepai/tunbert/)
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# how to load the model
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```python
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!git clone https://huggingface.co/not-lain/TunBERT
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!pip install transformers
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import torch.nn as nn
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import torch
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from transformers import AutoTokenizer, AutoModelForMaskedLM, AutoModelForSequenceClassification, PreTrainedModel,AutoConfig, BertModel
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from transformers.modeling_outputs import SequenceClassifierOutput
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config = AutoConfig.from_pretrained("not-lain/TunBERT")
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class classifier(nn.Module):
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def __init__(self,config):
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super().__init__()
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self.layer0 = nn.Linear(in_features=config.hidden_size, out_features=config.hidden_size, bias=True)
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self.layer1 = nn.Linear(in_features=config.hidden_size, out_features=config.type_vocab_size, bias=True)
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def forward(self,tensor):
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out1 = self.layer0(tensor)
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return self.layer1(out1)
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class TunBERT(PreTrainedModel):
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def __init__(self, config):
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super().__init__(config)
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self.BertModel = BertModel(config)
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self.dropout = nn.Dropout(p=0.1, inplace=False)
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self.classifier = classifier(config)
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def forward(self,input_ids=None,token_type_ids=None,attention_mask=None,labels=None) :
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outputs = self.BertModel(input_ids,token_type_ids,attention_mask)
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sequence_output = self.dropout(outputs.last_hidden_state)
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logits = self.classifier(sequence_output)
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loss =None
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if labels is not None :
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loss_func = nn.CrossentropyLoss()
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loss = loss_func(logits.view(-1,self.config.type_vocab_size),labels.view(-1))
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return SequenceClassifierOutput(loss = loss, logits= logits, hidden_states=outputs.last_hidden_state,attentions=outputs.attentions)
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tunbert = TunBERT(config)
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tunbert.load_state_dict(torch.load("/content/TunBERT/pytorch_model.bin"))
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tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")
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```
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# how to use the model
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```python
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text = "[insert text here]"
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inputs = tokenizer(text,return_tensors='pt')
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output = model(**inputs)
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```
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