# Lightweight text generation

This model is a GGUF format conversion version of Baidu's ERNIE-4.5-0.3B-PT, supporting Chinese and English text generation tasks.

Jan-nano-8bit is an 8-bit quantized version converted from the Menlo/Jan-nano model, optimized for the MLX framework and suitable for text generation tasks.

The Huihui AI Quantized Model is a quantized version of Magistral-Small-2506-abliterated, dedicated to making knowledge accessible to everyone.

This project provides a quantized version of Dobby-Mini-Unhinged-Plus-Llama-3.1-8B, aiming to make knowledge accessible to everyone.

Penny - 1.7B is a quantized version of a large language model dedicated to making knowledge accessible to everyone.

DMind-1-mini is a lightweight text generation model suitable for various natural language processing tasks.

This is a quantized version based on the Qwen3-0.6B-abliterated model, using llama.cpp for quantization, suitable for text generation tasks.

This repository contains GGUF format model files for Qwen/Qwen3-0.6B, quantized by TensorBlock's machines and compatible with llama.cpp.

GGUF quantized version of Qwen3-0.6B, suitable for text generation tasks.

Qwen2-96M is a miniature language model based on the Qwen2 architecture, containing 96 million parameters and supporting a context length of 8192 tokens, suitable for English text generation tasks.

Tessa-T1-3B is a 3B-parameter large language model based on the Qwen2 architecture, offering multiple quantization versions to accommodate different hardware requirements.

This is a quantized version in GGUF format based on the Llama-3.1-8B-RainbowLight-EtherealMix model, which facilitates the development of applications related to text generation.

The GGUF format file of the Qwen2.5-1.5B-Instruct model, suitable for text generation tasks.

Gemma-2-2b-it-abliterated is a 2.2B parameter language model based on the Google Gemma architecture, optimized through quantization for text generation tasks.

Gemma is a lightweight open model series launched by Google, built on the technology used to create Gemini models, suitable for various text generation tasks.

Gemma is a lightweight open-source large language model launched by Google, built with the same technology as Gemini, suitable for text generation tasks.

The 4-bit quantization version of Phi-3-mini-4k-instruct, quantized using the bitsandbytes tool, is designed specifically for fine-tuning.

This is a small randomly initialized model based on the Qwen1.5-MoE architecture, using float16 precision, suitable for text generation tasks.

phi-2-super-GGUF is the GGUF quantized version of the abacaj/phi-2-super model, suitable for local execution and text generation tasks.

Minueza-32M-Base is a base model with 32 million parameters, fully trained on extensive English text corpora, suitable for text generation tasks.

Gemma is a lightweight open-source large language model series launched by Google, built on the technology used to create Gemini models, offering a base version with 2 billion parameters.

A 200-million-parameter Chinese causal language model based on the Phi2 architecture, supporting text generation tasks

TinyLLama-v0 is a lightweight language model provided in GGUF format, suitable for text generation tasks.

Puma-3B is a text generation model fine-tuned based on OpenLLaMA 3B V2. It is trained on the ShareGPT Hyperfiltered dataset and is suitable for various text generation tasks.