From a282aec8142975b90aaeb7f430bac794a3657f19 Mon Sep 17 00:00:00 2001 From: Madeesh Kannan Date: Thu, 20 Jul 2023 12:54:43 +0200 Subject: [PATCH] Remove mentions of Torchscript and quantization Both are disabled in the initial release of `spacy-curated-transformers`. --- website/docs/api/architectures.mdx | 5 ----- website/docs/api/cli.mdx | 12 ------------ website/docs/api/curated-transformer.mdx | 2 +- 3 files changed, 1 insertion(+), 18 deletions(-) diff --git a/website/docs/api/architectures.mdx b/website/docs/api/architectures.mdx index cb217af15..86151c3fc 100644 --- a/website/docs/api/architectures.mdx +++ b/website/docs/api/architectures.mdx @@ -524,7 +524,6 @@ Construct an ALBERT transformer model. | `num_hidden_layers` | Number of hidden layers. ~~int~~ | | `padding_idx` | Index of the padding meta-token. ~~int~~ | | `type_vocab_size` | Type vocabulary size. ~~int~~ | -| `torchscript` | Set to `True` when loading TorchScript models, `False` otherwise. ~~bool~~ | | `mixed_precision` | Use mixed-precision training. ~~bool~~ | | `grad_scaler_config` | Configuration passed to the PyTorch gradient scaler. ~~dict~~ | | **CREATES** | The model using the architecture ~~Model[TransformerInT, TransformerOutT]~~ | @@ -553,7 +552,6 @@ Construct a BERT transformer model. | `num_hidden_layers` | Number of hidden layers. ~~int~~ | | `padding_idx` | Index of the padding meta-token. ~~int~~ | | `type_vocab_size` | Type vocabulary size. ~~int~~ | -| `torchscript` | Set to `True` when loading TorchScript models, `False` otherwise. ~~bool~~ | | `mixed_precision` | Use mixed-precision training. ~~bool~~ | | `grad_scaler_config` | Configuration passed to the PyTorch gradient scaler. ~~dict~~ | | **CREATES** | The model using the architecture ~~Model[TransformerInT, TransformerOutT]~~ | @@ -582,7 +580,6 @@ Construct a CamemBERT transformer model. | `num_hidden_layers` | Number of hidden layers. ~~int~~ | | `padding_idx` | Index of the padding meta-token. ~~int~~ | | `type_vocab_size` | Type vocabulary size. ~~int~~ | -| `torchscript` | Set to `True` when loading TorchScript models, `False` otherwise. ~~bool~~ | | `mixed_precision` | Use mixed-precision training. ~~bool~~ | | `grad_scaler_config` | Configuration passed to the PyTorch gradient scaler. ~~dict~~ | | **CREATES** | The model using the architecture ~~Model[TransformerInT, TransformerOutT]~~ | @@ -611,7 +608,6 @@ Construct a RoBERTa transformer model. | `num_hidden_layers` | Number of hidden layers. ~~int~~ | | `padding_idx` | Index of the padding meta-token. ~~int~~ | | `type_vocab_size` | Type vocabulary size. ~~int~~ | -| `torchscript` | Set to `True` when loading TorchScript models, `False` otherwise. ~~bool~~ | | `mixed_precision` | Use mixed-precision training. ~~bool~~ | | `grad_scaler_config` | Configuration passed to the PyTorch gradient scaler. ~~dict~~ | | **CREATES** | The model using the architecture ~~Model[TransformerInT, TransformerOutT]~~ | @@ -641,7 +637,6 @@ Construct a XLM-RoBERTa transformer model. | `num_hidden_layers` | Number of hidden layers. ~~int~~ | | `padding_idx` | Index of the padding meta-token. ~~int~~ | | `type_vocab_size` | Type vocabulary size. ~~int~~ | -| `torchscript` | Set to `True` when loading TorchScript models, `False` otherwise. ~~bool~~ | | `mixed_precision` | Use mixed-precision training. ~~bool~~ | | `grad_scaler_config` | Configuration passed to the PyTorch gradient scaler. ~~dict~~ | | **CREATES** | The model using the architecture ~~Model[TransformerInT, TransformerOutT]~~ | diff --git a/website/docs/api/cli.mdx b/website/docs/api/cli.mdx index 86a5d026d..c0a18085b 100644 --- a/website/docs/api/cli.mdx +++ b/website/docs/api/cli.mdx @@ -1054,18 +1054,6 @@ Token length range: [1, 8] ``` -## quantize {id="quantize",tag="command",version="3.6"} - -Quantize a curated transformers model to reduce its size. - -| Name | Description | -|----------------|---------------------------------------------------------------------| -| `model_path` | Model to quantize. ~~Path (positional)~~ | -| `output_path` | Output directory to store quantized model in. ~~Path (positional)~~ | -| `max_mse_loss` | Maximum MSE loss of quantized parameters. ~~float (option)~~ | -| `skip_embeds` | Do not quantize embeddings. ~~bool (option)~~ | -| `skip_linear` | Do not quantize linear layers. ~~bool (option)~~ | - ## train {id="train",tag="command"} Train a pipeline. Expects data in spaCy's diff --git a/website/docs/api/curated-transformer.mdx b/website/docs/api/curated-transformer.mdx index d5bc00112..c9e0dfb5c 100644 --- a/website/docs/api/curated-transformer.mdx +++ b/website/docs/api/curated-transformer.mdx @@ -25,7 +25,7 @@ work out-of-the-box. -This Python package provides a curated set of transformer models for spaCy. It is focused on deep integration into spaCy and will support deployment-focused features such as distillation and quantization. Curated transformers currently supports the following model types: +This Python package provides a curated set of transformer models for spaCy. It is focused on deep integration into spaCy and will support deployment-focused features such as distillation and quantization in the future. spaCy curated transformers currently supports the following model types: * ALBERT * BERT