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Building Cost-Efficient Enterprise RAG applications with Intel Gaudi 2 and Intel Xeon

May 9, 2024

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Intel's activity

n1ck-guo

updated a dataset about 9 hours ago

Intel/dynamic_model_information

Updated about 9 hours ago • 185

PhillipHoward

published a dataset 1 day ago

Intel/Uncovering_LVLM_Bias

Updated 1 day ago • 3

kylemin

updated a Space 2 days ago

UnlearnDiffAtk Benchmark

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ek-id

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Intel/polite-guard

Text Classification • Updated 7 days ago • 652 • 3

xinchen9

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UnlearnDiffAtk Benchmark

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ek-id

in Intel/polite-guard 8 days ago

Add ONNX file of this model

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mgustineli-intel

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bconsolvo

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Haihao

authored a paper 2 months ago

A dynamic parallel method for performance optimization on hybrid CPUs

Paper • 2411.19542 • Published Nov 29, 2024 • 5

daniel-de-leon

posted an update 4 months ago

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2406

As the rapid adoption of chat bots and QandA models continues, so do the concerns for their reliability and safety. In response to this, many state-of-the-art models are being tuned to act as Safety Guardrails to protect against malicious usage and avoid undesired, harmful output. I published a Hugging Face blog introducing a simple, proof-of-concept, RoBERTa-based LLM that my team and I finetuned to detect toxic prompt inputs into chat-style LLMs. The article explores some of the tradeoffs of fine-tuning larger decoder vs. smaller encoder models and asks the question if "simpler is better" in the arena of toxic prompt detection.

🔗 to blog: https://huggingface.co/blog/daniel-de-leon/toxic-prompt-roberta
🔗 to model: Intel/toxic-prompt-roberta
🔗 to OPEA microservice: https://github.com/opea-project/GenAIComps/tree/main/comps/guardrails/toxicity_detection

A huge thank you to my colleagues that helped contribute: @qgao007 , @mitalipo , @ashahba and Fahim Mohammad