This repository is based on https://github.com/jqueguiner/wav2vec2-sprint
Dockerhub available at https://hub.docker.com/r/patilsuraj/hf-wav2vec
to build the docker :
$ docker build -t hf-wav2vec-sprint -f Dockerfile .
to push it to dockerhub First create a repository on dockerhub
$ docker tag hf-wav2vec-sprint your-dockerhub-user/hf-wav2vec-sprint
to push it to dockerhub
$ docker push your-dockerhub-user/hf-wav2vec-sprint
Initialize your sweep from any machine...
$ export WANDB_API_KEY=YOUR_WANDB_API_KEY
$ export WANDB_ENTITY=YOUR_WANDB_ENTITY
$ export WANDB_PROJECT=YOUR_WANDB_PROJECT
$ wandb sweep sweep.yaml
... the execution above will give you a sweep id, save it and on the training machine run:
$ export WANDB_API_KEY=YOUR_WANDB_API_KEY
$ export WANDB_ENTITY=YOUR_WANDB_ENTITY
$ export WANDB_PROJECT=YOUR_WANDB_PROJECT
$ wandb agent YOUR_SWEEP_ID
You need to upload the following files to the HF repository
- preprocessor_config.json
- special_tokens_map.json
- tokenizer_config.json
- vocab.json
- config.json
- pytorch_model.bin
- README.md (create this file based on the MODEL_CARD.md)
$ git config --global user.email "[email protected]"
$ git config --global user.name "Your name"
$ transformers-cli login
$ transformers-cli repo create your-model-name
$ git clone https://username:[email protected]/username/your-model-name
$ git add .
$ git commit -m "Initial commit"
$ git push
- audioread.exceptions.NoBackendError:
$ sudo apt-get install ffmpeg sox libsox-fmt-mp3