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Shivam Sharma

NNEngine
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AI & ML interests

AI & ML engineer

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reacted to codelion's post with 🔥 3 days ago
Perplexity released a dataset (BrowseSafe) and benchmark to catch and prevent malicious prompt-injection instructions in real-time. We trained a prompt injection classifier on BrowseSafe using adaptive-classifier with ModernBERT-base embeddings. 74.9% F1 on detecting prompt injection in web content. Model -> https://huggingface.co/adaptive-classifier/browsesafe Dataset -> https://huggingface.co/datasets/perplexity-ai/browsesafe-bench Repo -> https://github.com/codelion/adaptive-classifier
upvoted an article 3 days ago
Ellora: Enhancing LLMs with LoRA - Standardized Recipes for Capability Enhancement
reacted to codelion's post with 🚀 3 days ago
Recently, Essential AI released a new 8B base model https://huggingface.co/EssentialAI/rnj-1 they highlighted the importance of data mix for pretraning - "In the long run, we expect our methods to automatically represent, transform, and blend data to optimize measurable abilities in pre-training. Our work on modeling data taxonomies led to new approaches for jointly clustering and mixing data distributions under data repetition penalties. Many improvements in our STEM abilities can be traced back to this. " This resonates with the recent work we did around optimal dataset mixing for pretraining where we saw have the right mix can increase the efficiency of training - https://huggingface.co/blog/codelion/optimal-dataset-mixing
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