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