Fixed compiling issue, added legnth penalty, and atttempting freezing encoder layers 0-5 to lower parameters and preserve T5's langauge understanding.

Improve emotion task architecture and fix visualizations

Clean up codebase and fix training bugs

Update LexiMind: improved training, model architecture, and evaluation

Fix Pylance type errors, add inductor compilation support

Full training run, code cleanup, mypy/ruff fixes

feat: Add FLAN-T5 compatibility with relative position bias

Build: Pin ruff to v0.4.4 in pre-commit to match CI

Refactor: Fix B905 zip() strictness and resolve mypy error in evaluate.py

Fix: Resolve mypy type errors and configuration

Chore: Update pre-commit hooks and fix formatting

Style: Fix formatting for models and tests

Style: Apply ruff formatting

Style: Fix linting errors and organize imports (ruff & mypy)

Refactor: Consolidate dependencies, improve testing, and add CI/CD

refactor: update training code, history and remove large checkpoint to fix storage limit

Added pretrained BART wights for the encoder/decoder while keeping custom architectiure and task heads

Summarization fix

Summarization fix

Updated Greedy Decode w/ a minlen search

chore: snapshot current refinements

Updated Summarizer, Preprocessor to run on my custom transformer and added basic streamlit frontend demo

Finsihed Decoder Implementation, as well as prediction heads and multitask

Implemented the following parts for the Transformer model: poisional_encoding, feedfoward, encoder, and skeleton of decoder. As well as Test cases for each class respectively and visualizations

Implemented ScaledDotProduct Attention and Multi-Head Attention

Reformatted Project Structure