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---
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license: apache-2.0
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datasets:
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- google/wiki40b
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language:
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- zh
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base_model:
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- openai-community/gpt2
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---
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# Dorami
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A GPT-based pretrained model using the BERT Tokenizer
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## Model description
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### Training data
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[google/wiki40b](https://huggingface.co/datasets/google/wiki40b)
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### Training code
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[dorami](https://github.com/6zeus/dorami.git)
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## How to use
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### 1. Download model from Hugging Face Hub to local
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```
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git lfs install
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git clone https://huggingface.co/lucky2me/Dorami
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```
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### 2. Use the model downloaded above
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```python
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import torch
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from transformers import AutoTokenizer,AutoModelForCausalLM
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model_path = "The path of the model downloaded above"
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tokenizer = AutoTokenizer.from_pretrained(model_path)
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model = AutoModelForCausalLM.from_pretrained(model_path)
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text = "fill in any text you like."
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encoded_input = tokenizer(text, return_tensors='pt')
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output = model(**encoded_input)
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predicted_token_id = torch.argmax(output.logits[:, -1, :], dim=-1)
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decoded_text = tokenizer.decode(predicted_token_id, skip_special_tokens=True)
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print("decoded text:",decoded_text)
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``` |
