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README.md
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```python
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from transformers import GPTNeoXForCausalLM, AutoTokenizer
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tokenizer = AutoTokenizer.from_pretrained("afterless/reverse-pythia-160m")
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model = GPTNeoXForCausalLM.from_pretrained("afterless/reverse-pythia-160m")
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inputs = tokenizer(
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inputs['input_ids'] = t.flip(inputs.input_ids, (1,))
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tokens = t.flip(model.generate(**inputs), (1,))
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tokenizer.decode(tokens[0])
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---
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datasets:
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- EleutherAI/pile
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language:
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- en
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tags:
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- Text Generation
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- pytorch
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- causal-lm
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---
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```python
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from transformers import GPTNeoXForCausalLM, AutoTokenizer
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tokenizer = AutoTokenizer.from_pretrained("afterless/reverse-pythia-160m")
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model = GPTNeoXForCausalLM.from_pretrained("afterless/reverse-pythia-160m")
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inputs = tokenizer(
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"but I told him, the cheese was the best",
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return_token_type_ids=False,
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return_tensors="pt"
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)
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inputs['input_ids'] = t.flip(inputs.input_ids, (1,))
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tokens = t.flip(model.generate(**inputs), (1,))
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tokenizer.decode(tokens[0])
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