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Recent Posts
- ~30% Compression Of LLM (Flan-T5-Base) With Low Rank Decomposition Of Attention Weight Matrices
- Adapter Based Fine Tuning BART And T5-Flan-XXL For Single Word Spell Correction
- Revamping Dual Encoder Model Architecture: A layered approach to fuse multi-modal features and plug-and-play integration of Encoders
- Summary Of Adapter Based Performance Efficient Fine Tuning (PEFT) Techniques For Large Language Models
- Neural Ranking Architectures
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Monthly Archives: April 2023
Revamping Dual Encoder Model Architecture: A layered approach to fuse multi-modal features and plug-and-play integration of Encoders
Code examples of feature fusion techniques and tower encoders in last half of the blog In Embedding Based Retrieval(EBR) we create embedding of search query in an online manner and then find k-nearest neighbors of the query vector in an … Continue reading
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Summary Of Adapter Based Performance Efficient Fine Tuning (PEFT) Techniques For Large Language Models
The two most common transfer learning techniques in NLP were feature-based transfer (generating input text embedding from a pre-trained large model and using it as a feature in your custom model) and fine-tuning (fine tuning the pre-trained model on custom … Continue reading
Posted in performance efficient fine tuning, Uncategorized
Tagged adapters, gpt, large language model, llama, lora, machine learning, nlp, peft
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Neural Ranking Architectures
Glimpses On Implicit/Explicit, Dense/Sparse, Gated/Non Gated, Low Rank And Many More Layered Interactions 101 Ranking Model Architecture Neural ranking models are the most important component in multi stage retrieval and ranking pipeline. Whether it is e-commerce search, ads targeting, music search or … Continue reading