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doc: simplify installation instructions
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- dev/{seq2seq/environment.yaml → environment.yaml} +0 -0
- dev/seq2seq/requirements.txt +0 -15
README.md
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@@ -24,23 +24,11 @@ Refer to [our report](https://wandb.ai/dalle-mini/dalle-mini/reports/DALL-E-mini
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## Development
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This section is for the adventurous people wanting to look into the code.
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### Dependencies Installation
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The root folder and associated `requirements.txt` is only for the app.
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You should create a new python virtual environment and install the project dependencies inside the virtual env. You need to use the `-f` (`--find-links`) option for `pip` to be able to find the appropriate `libtpu` required for the TPU hardware.
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Adapt the installation to your own hardware and follow library installation instructions.
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```
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$ pip install -r requirements.txt -f https://storage.googleapis.com/jax-releases/libtpu_releases.html
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```
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If you use `conda`, you can create the virtual env and install everything using: `conda env update -f environments.yaml`
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### Training of VQGAN
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## Development
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### Dependencies Installation
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The root folder and associated `requirements.txt` is only for the app.
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For development, use ['dev/requirements.txt`](dev/requirements.txt) or ['dev/environment.yaml`](dev/environment.yaml).
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### Training of VQGAN
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dev/{seq2seq/environment.yaml → environment.yaml}
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dev/seq2seq/requirements.txt
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# Note: install with the following command:
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# pip install -r requirements.txt -f https://storage.googleapis.com/jax-releases/libtpu_releases.html
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# Otherwise it won't find the appropriate libtpu_nightly
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requests
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jax[tpu]>=0.2.16
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-e git+https://github.com/huggingface/transformers.git@master#egg=transformers
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-e git+https://github.com/huggingface/datasets.git@master#egg=datasets
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flax
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jupyter
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wandb
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nltk
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optax
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# Inference
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ftfy
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