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🖍 remove broken link (#15615)

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Steven Liu
2022-02-11 12:33:55 -06:00
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@@ -38,10 +38,10 @@ Tips:
- CTRL was trained with a causal language modeling (CLM) objective and is therefore powerful at predicting the next - CTRL was trained with a causal language modeling (CLM) objective and is therefore powerful at predicting the next
token in a sequence. Leveraging this feature allows CTRL to generate syntactically coherent text as it can be token in a sequence. Leveraging this feature allows CTRL to generate syntactically coherent text as it can be
observed in the *run_generation.py* example script. observed in the *run_generation.py* example script.
- The PyTorch models can take the *past* as input, which is the previously computed key/value attention pairs. Using - The PyTorch models can take the `past_key_values` as input, which is the previously computed key/value attention pairs.
this *past* value prevents the model from re-computing pre-computed values in the context of text generation. See TensorFlow models accepts `past` as input. Using the `past_key_values` value prevents the model from re-computing
[reusing the past in generative models](../quickstart#using-the-past) for more information on the usage of pre-computed values in the context of text generation. See the [`forward`](model_doc/ctrl#transformers.CTRLModel.forward)
this argument. method for more information on the usage of this argument.
This model was contributed by [keskarnitishr](https://huggingface.co/keskarnitishr). The original code can be found This model was contributed by [keskarnitishr](https://huggingface.co/keskarnitishr). The original code can be found
[here](https://github.com/salesforce/ctrl). [here](https://github.com/salesforce/ctrl).