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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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|
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tokenizer = AutoTokenizer.from_pretrained( |
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"afterless/reverse-pythia-160m" |
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) |
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model = GPTNeoXForCausalLM.from_pretrained( |
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"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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``` |
