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Update README.md
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README.md
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@@ -16,8 +16,8 @@ We pruned its vocabulary from 250880 to 46145 with Chinese corpus to reduce GPU
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```python
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from transformers import BloomTokenizerFast, BloomForCausalLM
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tokenizer = BloomTokenizerFast.from_pretrained('Langboat/bloom-
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model = BloomForCausalLM.from_pretrained('Langboat/bloom-
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print(tokenizer.batch_decode(model.generate(tokenizer.encode('中国的首都是', return_tensors='pt'))))
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```
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```python
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from transformers import BloomTokenizerFast, BloomForCausalLM
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tokenizer = BloomTokenizerFast.from_pretrained('Langboat/bloom-1b4-zh')
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model = BloomForCausalLM.from_pretrained('Langboat/bloom-1b4-zh')
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print(tokenizer.batch_decode(model.generate(tokenizer.encode('中国的首都是', return_tensors='pt'))))
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```
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