Building a Bigram Language Model From Scratch
📰 Medium · LLM
Learn to build a bigram language model from scratch using a tiny neural network and understand probabilities and negative log-likelihood
Action Steps
- Build a bigram language model using a tiny neural network
- Calculate probabilities of word sequences
- Apply negative log-likelihood to evaluate model performance
- Generate new names using the trained model
- Compare model performance with different architectures
Who Needs to Know This
NLP engineers and data scientists can benefit from this article to improve their language modeling skills and apply them to real-world problems
Key Insight
💡 Bigram language models can be used to generate new text based on probability distributions
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🤖 Build a bigram language model from scratch and generate new names! #LLM #NLP
Key Takeaways
Learn to build a bigram language model from scratch using a tiny neural network and understand probabilities and negative log-likelihood
Full Article
Understanding probabilities, negative log-likelihood, and a tiny neural network by generating new names Continue reading on Medium »
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