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zeekay cb4a7af933 Merge remote-tracking branch 'origin/chore/purge-zama-brand-v2'

# Conflicts:
#	.github/workflows/benchmarks.yaml
#	.github/workflows/cifar_benchmark.yaml
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#	.github/workflows/llama_finetuning_benchmark.yaml
#	.github/workflows/publish_aws_ami.yaml
#	.github/workflows/release.yaml
#	.github/workflows/resnet_hybrid_model.yaml
#	.github/workflows/sync_on_push.yaml
#	.github/workflows/weekly_tests.yaml
#	LICENSE
#	Makefile
#	README.md
#	UPGRADING.md
#	benchmarks/common.py
#	ci/aws_ami_build_component.yaml
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#	docs/advanced_examples/ClassifierComparison.ipynb
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#	docs/advanced_examples/FullyConnectedNeuralNetworkOnMNIST.ipynb
#	docs/advanced_examples/GLMComparison.ipynb
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#	docs/advanced_examples/utils/classifier_comparison_utils.py
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#	docs/deep-learning/fhe_friendly_models.md
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#	use_case_examples/lora_finetuning/data_finetune/what_is_fhe.txt
#	use_case_examples/sentiment_analysis_with_transformer/SentimentClassification.ipynb
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#	use_case_examples/titanic/README.md
#	use_case_examples/white_paper_experiment/WhitePaperExperiments.ipynb

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Makefile

Initial commit: Lux FHE ML SDK

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README.md

docs+brand: continue Zama/Fhenix purge — luxfhe-ai artefacts, URLs, HF demos

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requirements.txt

chore(brand): purge Zama refs across docs, README, configs — phase 1

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SentimentClassification.ipynb

chore(brand): purge Zama refs across docs, README, configs — phase 1

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README.md

Sentiment Analysis With FHE

Running the application on your machine

Please see the hugging face space that runs the application along with the code if you want to run this locally on your machine or deploy this following a client/server framework.

Installation

To use this code, you need to have Python 3.8 and install the following dependencies:

pip install -r requirements.txt

Training a new model

The notebook SentimentClassification.ipynb provides a way to train a new model.