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reverse-pythia-160m

Text Generation
Transformers
PyTorch
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gpt_neox
Text Generation
causal-lm
text-generation-inference
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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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  ```python
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  from transformers import GPTNeoXForCausalLM, AutoTokenizer
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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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+ )
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  inputs = tokenizer(
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  "but I told him, the cheese was the best",