[doc] Model upload and sharing
ping @lysandrejik @thomwolf Is this clear enough? Anything we should add?
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README.md
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README.md
@@ -56,6 +56,7 @@ Choose the right framework for every part of a model's lifetime
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| [Quick tour: Usage](#quick-tour) | Tokenizers & models usage: Bert and GPT-2 |
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| [Quick tour: TF 2.0 and PyTorch ](#Quick-tour-TF-20-training-and-PyTorch-interoperability) | Train a TF 2.0 model in 10 lines of code, load it in PyTorch |
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| [Quick tour: Fine-tuning/usage scripts](#quick-tour-of-the-fine-tuningusage-scripts) | Using provided scripts: GLUE, SQuAD and Text generation |
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| [Quick tour: Share your models ](#Quick-tour-of-model-sharing) | Upload and share your fine-tuned models with the community |
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| [Migrating from pytorch-transformers to transformers](#Migrating-from-pytorch-transformers-to-transformers) | Migrating your code from pytorch-transformers to transformers |
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| [Migrating from pytorch-pretrained-bert to pytorch-transformers](#Migrating-from-pytorch-pretrained-bert-to-transformers) | Migrating your code from pytorch-pretrained-bert to transformers |
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| [Documentation][(v2.2.0/v2.2.1/v2.2.2)](https://huggingface.co/transformers/v2.2.0) [(v2.1.1)](https://huggingface.co/transformers/v2.1.1) [(v2.0.0)](https://huggingface.co/transformers/v2.0.0) [(v1.2.0)](https://huggingface.co/transformers/v1.2.0) [(v1.1.0)](https://huggingface.co/transformers/v1.1.0) [(v1.0.0)](https://huggingface.co/transformers/v1.0.0) [(master)](https://huggingface.co/transformers) | Full API documentation and more |
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@@ -446,6 +447,46 @@ python ./examples/run_generation.py \
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--repetition_penalty=1.2 \
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```
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## Quick tour of model sharing
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New in `v2.2.2`: you can now upload and share your fine-tuned models with the community, using the <abbr title="Command-line interface">CLI</abbr> that's built-in to the library.
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**First, create an account on [https://huggingface.co/join](https://huggingface.co/join)**. Then:
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```shell
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transformers-cli login
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# log in using the same credentials as on huggingface.co
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```
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Upload your model:
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```shell
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transformers-cli upload ./path/to/pretrained_model/
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# ^^ Upload folder containing weights/tokenizer/config
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# saved via `.save_pretrained()`
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transformers-cli upload ./config.json [--filename foobar.json]
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# ^^ Upload a single file
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# (you can optionally override its filename)
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```
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Your model will then be accessible through its identifier:
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```python
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"username/model_name"
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```
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Anyone can load it from code:
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```python
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tokenizer = AutoTokenizer.from_pretrained("username/model_name")
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model = AutoModel.from_pretrained("username/model_name")
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```
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Finally, list all your files on S3:
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```shell
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transformers-cli ls
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# List all your S3 objects.
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```
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## Migrating from pytorch-transformers to transformers
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Here is a quick summary of what you should take care of when migrating from `pytorch-transformers` to `transformers`.
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