Instructions to use junnyu/roformer_chinese_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- paddlenlp
How to use junnyu/roformer_chinese_base with paddlenlp:
from paddlenlp.transformers import AutoTokenizer, RoFormerForMaskedLM tokenizer = AutoTokenizer.from_pretrained("junnyu/roformer_chinese_base", from_hf_hub=True) model = RoFormerForMaskedLM.from_pretrained("junnyu/roformer_chinese_base", from_hf_hub=True) - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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git clone https://github.com/JunnYu/RoFormer_pytorch
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cd RoFormer_pytorch
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import torch
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from model import
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tokenizer = RoFormerTokenizer.from_pretrained("junnyu/roformer_chinese_base")
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model =
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inputs = tokenizer(text, return_tensors="pt")
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with torch.no_grad():
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outputs = model(**inputs).
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```
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## 引用
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git clone https://github.com/JunnYu/RoFormer_pytorch
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cd RoFormer_pytorch
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import torch
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from model import RoFormerForMaskedLM, RoFormerTokenizer
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text = "今天[MASK]很好,我[MASK]去公园玩。"
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tokenizer = RoFormerTokenizer.from_pretrained("junnyu/roformer_chinese_base")
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model = RoFormerForMaskedLM.from_pretrained("junnyu/roformer_chinese_base")
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inputs = tokenizer(text, return_tensors="pt")
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with torch.no_grad():
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outputs = model(**inputs).logits[0]
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outputs_sentence = ""
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for i, id in enumerate(tokenizer.encode(text)):
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if id == tokenizer.mask_token_id:
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tokens = tokenizer.convert_ids_to_tokens(outputs[i].topk(k=5)[1])
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outputs_sentence += "[" + "||".join(tokens) + "]"
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else:
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outputs_sentence += "".join(
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tokenizer.convert_ids_to_tokens([id], skip_special_tokens=True))
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print(outputs_sentence)
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# 今天[天气||天||心情||阳光||空气]很好,我[想||要||打算||准备||喜欢]去公园玩。
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```
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## 引用
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