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blog.context.ai | ||
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www.superannotate.com
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| | | | | Dive into LLM fine-tuning: its importance, types, methods, and best practices for optimizing language model performance. | |
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tty4.dev
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| | | | | Building Retrieval-augmented generation (RAG) is hard. At least if you want to get helpful and reliable results. | |
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lmsys.org
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| | | | | We introduce Vicuna-13B, an open-source chatbot trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT. Preliminary evaluation ... | |
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unstructured.io
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| | | Navigate the Massive Text Embedding Benchmark (MTEB) leaderboard with confidence! Understand the difference between Bi-Encoders and Cross-Encoders, learn how text embedding models are pre-trained and benchmarked, and how to make the best choice for your specific use case. | ||
