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James Sorrels

jme23

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DavidAU/Maximizing-Model-Performance-All-Quants-Types-And-Full-Precision-by-Samplers_Parameters

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liked a model 29 days ago

DavidAU/Maximizing-Model-Performance-All-Quants-Types-And-Full-Precision-by-Samplers_Parameters

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liked a dataset 4 months ago

silverbelt/upscaler-gallery

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New activity in city96/t5-v1_1-xxl-encoder-gguf 4 months ago

how do I use this can't load t5 gguf with clip l safetensor

#6 opened 4 months ago by

MANOFAi94

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XLabs-AI/flux-controlnet-collections

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XLabs-AI/flux-lora-collection

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reacted to louisbrulenaudet's post with 👍 5 months ago

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🚀 RAGoon is now available on PyPI, GitHub, and as a Space on Hugging Face for batched embeddings generation 🤗

RAGoon is a set of NLP utilities for multi-model embedding production, high-dimensional vector visualization, and aims to improve language model performance by providing contextually relevant information through search-based querying, web scraping and data augmentation techniques.

At this stage, 5 major classes are available via RAGoon to facilitate:
- the production of chain embeddings for several models to simplify a continuous deployment process;
- production of LLM requests for web querying and content retrieval via the Google API;
- recursive chunking via tokens;
- data visualization and the function to load embeddings from a FAISS index, reduce their dimensionality using PCA and/or t-SNE, and visualize them in an interactive 3D graph;
- the creation of binary indexes for search with scalar (int8) rescoring.

Link to GitHub: https://github.com/louisbrulenaudet/ragoon
Link to the 🤗 Space: louisbrulenaudet/ragoon