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metadata
language: en
tags:
  - azbert
  - pretraining
  - fill-mask
widget:
  - text: $f$ $($ $x$ [MASK] $y$ $)$
    example_title: mathy
  - text: $x$ [MASK] $x$ $equal$ $2$ $x$
    example_title: mathy
  - text: Proof by [MASK] that $n$ $fact$ $gt$ $3$ $n$ for $n$ $gt$ $6$
    example_title: mathy
  - text: Proof by induction that $n$ [MASK] $gt$ $3$ $n$ for $n$ $gt$ $6$
    example_title: mathy
  - text: The goal of life is [MASK].
    example_title: philosophical
license: mit

About

This repository is a boilerplate to push a mask-filling model to the HuggingFace Model Hub.

Upload to huggingface

Download your tokenizer, model checkpoints, and optionally the training logs () to the ./ckpt directory.

Optionally, test model using the MLM task:

pip install pya0
python test.py --test_file test.txt

Note
Modify the test examples in test.txt to play with it. The test file is tab-separated, the first column is additional positions you want to mask for the right-side sentence (useful for masking tokens in math markups). A zero means no additional mask positions.

To upload to huggingface, use the upload2hgf.sh script. Before runnig this script, be sure to check:

  • git-lfs is installed
  • having git-remote named hgf reference to https://huggingface.co/your/repo
  • model contains all the files needed: config.json and pytorch_model.bin
  • tokenizer contains all the files needed: added_tokens.json, special_tokens_map.json, tokenizer_config.json, vocab.txt and tokenizer.json
  • no tokenizer_file field in tokenizer_config.json (sometimes it is located locally at ~/.cache)