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typo fixes
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@ -161,7 +161,7 @@ run [`spacy pretrain`](/api/cli#pretrain).
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| `dropout` | The dropout rate. ~~float~~ | `0.2` |
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| `dropout` | The dropout rate. ~~float~~ | `0.2` |
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| `n_save_every` | Saving frequency. ~~int~~ | `null` |
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| `n_save_every` | Saving frequency. ~~int~~ | `null` |
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| `batch_size` | The batch size or batch size [schedule](https://thinc.ai/docs/api-schedules). ~~Union[int, Sequence[int]]~~ | `3000` |
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| `batch_size` | The batch size or batch size [schedule](https://thinc.ai/docs/api-schedules). ~~Union[int, Sequence[int]]~~ | `3000` |
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| `seed` | The random seed. ~~int~~ | `${system.seed}` |
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| `seed` | The random seed. ~~int~~ | `${system:seed}` |
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| `use_pytorch_for_gpu_memory` | Allocate memory via PyTorch. ~~bool~~ | `${system:use_pytorch_for_gpu_memory}` |
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| `use_pytorch_for_gpu_memory` | Allocate memory via PyTorch. ~~bool~~ | `${system:use_pytorch_for_gpu_memory}` |
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| `tok2vec_model` | tok2vec model section in the config. ~~str~~ | `"components.tok2vec.model"` |
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| `tok2vec_model` | tok2vec model section in the config. ~~str~~ | `"components.tok2vec.model"` |
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| `objective` | The pretraining objective. ~~Dict[str, Any]~~ | `{"type": "characters", "n_characters": 4}` |
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| `objective` | The pretraining objective. ~~Dict[str, Any]~~ | `{"type": "characters", "n_characters": 4}` |
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@ -144,7 +144,7 @@ https://github.com/explosion/spaCy/blob/develop/spacy/default_config.cfg
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Under the hood, the config is parsed into a dictionary. It's divided into
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Under the hood, the config is parsed into a dictionary. It's divided into
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sections and subsections, indicated by the square brackets and dot notation. For
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sections and subsections, indicated by the square brackets and dot notation. For
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example, `[training]` is a section and `[training.batch_size]` a subsections.
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example, `[training]` is a section and `[training.batch_size]` a subsection.
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Subsections can define values, just like a dictionary, or use the `@` syntax to
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Subsections can define values, just like a dictionary, or use the `@` syntax to
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refer to [registered functions](#config-functions). This allows the config to
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refer to [registered functions](#config-functions). This allows the config to
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not just define static settings, but also construct objects like architectures,
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not just define static settings, but also construct objects like architectures,
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@ -156,7 +156,7 @@ sections of a config file are:
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| `nlp` | Definition of the `nlp` object, its tokenizer and [processing pipeline](/usage/processing-pipelines) component names. |
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| `nlp` | Definition of the `nlp` object, its tokenizer and [processing pipeline](/usage/processing-pipelines) component names. |
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| `components` | Definitions of the [pipeline components](/usage/processing-pipelines) and their models. |
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| `components` | Definitions of the [pipeline components](/usage/processing-pipelines) and their models. |
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| `paths` | Paths to data and other assets. Re-used across the config as variables, e.g. `${paths:train}`, and can be [overwritten](#config-overrides) on the CLI. |
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| `paths` | Paths to data and other assets. Re-used across the config as variables, e.g. `${paths:train}`, and can be [overwritten](#config-overrides) on the CLI. |
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| `system` | Settings related to system and hardware. Re-used across the config as variables, e.g. `${system.seed}`, and can be [overwritten](#config-overrides) on the CLI. |
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| `system` | Settings related to system and hardware. Re-used across the config as variables, e.g. `${system:seed}`, and can be [overwritten](#config-overrides) on the CLI. |
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| `training` | Settings and controls for the training and evaluation process. |
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| `training` | Settings and controls for the training and evaluation process. |
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| `pretraining` | Optional settings and controls for the [language model pretraining](#pretraining). |
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| `pretraining` | Optional settings and controls for the [language model pretraining](#pretraining). |
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