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Dreamgen Lucid V1 Nemo GGUF

Developed by bartowski
A quantized model based on dreamgen/lucid-v1-nemo, processed with llama.cpp for various quantization levels, suitable for text generation tasks.
Downloads 6,593
Release Time : 4/17/2025

Model Overview

This model is a quantized version of dreamgen/lucid-v1-nemo, processed with llama.cpp for multiple precision levels, ideal for running in resource-constrained environments while maintaining high-quality text generation.

Model Features

Multiple Quantization Options
Offers various quantization options from BF16 to Q2_K to meet different hardware and performance needs.
Embedding and Output Weight Optimization
Certain quantization methods (e.g., Q3_K_XL, Q4_K_L) specially optimize embeddings and output weights to enhance model performance.
Online Repacking Functionality
Supports online weight repacking to optimize efficiency for ARM and AVX hardware.

Model Capabilities

Text Generation
Quantized Inference

Use Cases

Text Generation
Creative Writing
Used for generating creative texts such as stories, poems, etc.
Dialogue Systems
Used for building dialogue systems to generate natural language responses.
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