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2023-09-04 12:15:12 +02:00
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docs/source/en/generation_strategies.md
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@@ -92,7 +92,7 @@ sequences that start with a lower probability initial tokens and would've been i
- `do_sample`: if set to `True`, this parameter enables decoding strategies such as multinomial sampling, beam-search
multinomial sampling, Top-K sampling and Top-p sampling. All these strategies select the next token from the probability
distribution over the entire vocabulary with various strategy-specific adjustments.
- `num_return_sequences`: the number of sequence candidates to return for each input. This options is only available for
- `num_return_sequences`: the number of sequence candidates to return for each input. This option is only available for
the decoding strategies that support multiple sequence candidates, e.g. variations of beam search and sampling. Decoding
strategies like greedy search and contrastive search return a single output sequence.
@@ -146,7 +146,7 @@ one for summarization with beam search). You must have the right Hub permissions
## Streaming
The `generate()` supports streaming, through its `streamer` input. The `streamer` input is compatible any instance
The `generate()` supports streaming, through its `streamer` input. The `streamer` input is compatible with any instance
from a class that has the following methods: `put()` and `end()`. Internally, `put()` is used to push new tokens and
`end()` is used to flag the end of text generation.
@@ -301,7 +301,7 @@ the `num_beams` greater than 1, and set `do_sample=True` to use this decoding st
The diverse beam search decoding strategy is an extension of the beam search strategy that allows for generating a more diverse
set of beam sequences to choose from. To learn how it works, refer to [Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Models](https://arxiv.org/pdf/1610.02424.pdf).
This approach has three main parameters: `num_beams`, `num_beam_groups`, and `diversity_penalty`.
The diversily penalty ensures the outputs are distinct across groups, and beam search is used within each group.
The diversity penalty ensures the outputs are distinct across groups, and beam search is used within each group.
```python
@@ -367,7 +367,7 @@ To enable assisted decoding, set the `assistant_model` argument with a model.
['Alice and Bob are sitting in a bar. Alice is drinking a beer and Bob is drinking a']
```
When using assisted decoding with sampling methods, you can use the `temperarure` argument to control the randomness
When using assisted decoding with sampling methods, you can use the `temperature` argument to control the randomness
just like in multinomial sampling. However, in assisted decoding, reducing the temperature will help improving latency.
```python