Comments (1)
Hey @programarivm unfortunately Rubix ML does not make a good base library for a language generation project in my opinion. The reason is because language generation models, like the autoregressive type that predict the next word) tend to require a ton of computation especially at training but inference as well. Single-threaded CPU with additional PHP overhead would take forever to train. Additionally, we do not provide support for Transformers which is the current state-of-the-art neural network architecture at tackling these language generation problems.
I would take a look at fine-tuning a pretrained GPT with your chess-oriented corpus using PyTorch for your problem.
Where Rubix ML may be able to help you is in predicting intent from text. With that, you could respond with pregenerated text appropriately. This may or may not make your answers sound less robotic. It may even make it worse.
Hope all is well with you! Keep up the great work.
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Related Issues (20)
- Question, which model users for Fraud Prediction HOT 2
- Incorrect SVC save/load methods implementation HOT 2
- psr/log old version is limiting the project to be used on modern frameworks HOT 2
- Which alogorithm can be used for search result ranking ? HOT 2
- Is "Transformer Architecture Marchine Learning Model" supported on RubixML ??? HOT 4
- Map method in Dataset doesn't exist HOT 2
- Multi Language Tokenization Support HOT 3
- WordCountVectorizer Memory Issue HOT 2
- TruncatedSVD() made PHP crash without any message HOT 3
- Evaluation of the cluster quality with indicators HOT 1
- Requirements not resolved to an installable set of packages HOT 3
- Softmax Classifier & partial training HOT 1
- Convert `Transformers\PrincipalComponentAnalysis` to NumPower
- Convert `Transformers\LinearDiscriminantAnalysis` to NumPower
- Convert `Transformers\TruncatedSVD` to NumPower
- Convert `Generators\Blob` to NumPower
- Convert `Generators\Circle` to NumPower
- Convert `Generators\HalfMoon` to NumPower
- Add numpower to the GitHub workflow pipeline
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