Instructions to use voidful/albert_chinese_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use voidful/albert_chinese_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="voidful/albert_chinese_base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("voidful/albert_chinese_base") model = AutoModelForMaskedLM.from_pretrained("voidful/albert_chinese_base") - Notebooks
- Google Colab
- Kaggle
update readme
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README.md
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@@ -28,7 +28,7 @@ from transformers import AutoTokenizer, AlbertForMaskedLM
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import torch
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from torch.nn.functional import softmax
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pretrained = '
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tokenizer = AutoTokenizer.from_pretrained(pretrained)
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model = AlbertForMaskedLM.from_pretrained(pretrained)
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import torch
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from torch.nn.functional import softmax
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pretrained = 'voidful/albert_chinese_base'
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tokenizer = AutoTokenizer.from_pretrained(pretrained)
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model = AlbertForMaskedLM.from_pretrained(pretrained)
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