This is a lightweight text generation model based on the Meta LLaMA 3 8B model. It is efficiently fine-tuned using the Unsloth framework and converted to the GGUF format. The model is optimized for the Alpaca dataset, suitable for local deployment and inference, especially in resource-constrained environments.

Natural Language ProcessingGguf

Gemma 3 is a lightweight open-source multimodal model launched by Google. This version is an instruction-tuned quantization-aware training model with 12B parameters, which has been converted to the MXFP4 format of the MLX framework. It supports text and image input and generates text output, with a 128K context window and support for over 140 languages.

MultimodalMlx

EmbeddingGemma 300M 4bit is a lightweight text embedding model developed by Google, specifically optimized for the MLX framework. This model can convert text into high-quality vector representations and is suitable for various natural language processing tasks, especially sentence similarity calculation and feature extraction.

Natural Language ProcessingSentence-transformers

This is a 4-bit quantized version of Google's Gemma 3 270M Instruct model, specifically optimized for Apple chips using the MLX framework. This model is a lightweight yet powerful language model suitable for various text generation tasks and participates in the LM Studio Community Model Highlights Program.

Natural Language ProcessingTransformers

A lightweight language model developed by mistralai, optimized with 6-bit quantization via the MLX framework, specifically designed for Apple Silicon.

Natural Language ProcessingMlxMultiple Languages

TreeHop is a lightweight embedding-level framework designed for efficient query embedding generation and filtering in multi-hop QA, significantly reducing computational overhead.

Natural Language ProcessingSafetensors

4-bit quantized version based on Qwen3-1.7B, a lightweight large language model optimized for the MLX framework

Natural Language ProcessingSafetensors

MiniLLM is a lightweight Chinese language model developed based on the bert4torch framework, covering the entire process from pre-training to instruction fine-tuning, with basic dialogue capabilities

Natural Language ProcessingTransformers

bert-lite is a lightweight natural language processing model optimized based on the BERT framework, designed for low-resource environments and suitable for tasks like MNLI and NLI.

Natural Language ProcessingTransformersEnglish

SmolDocling-256M-preview-mlx-bf16 is a lightweight vision-language model converted from SmolDocling-256M-preview, specifically designed for document image understanding and conversion. This model is optimized using the MLX framework and supports converting document images into the structured DocTags format.

MultimodalTransformersEnglish

MiniVLA is a lightweight vision-language model compatible with the Prismatic VLMs training framework, supporting multimodal tasks from image-text to text.

MultimodalTransformersEnglish

This is a 4-bit quantized version converted from the Qwen2.5-Coder-0.5B-Instruct model, specifically optimized for the Apple MLX framework. This model is a lightweight code generation model with 0.5B parameters, supporting code generation and programming-related tasks.

Natural Language ProcessingTransformersMultiple Languages

This is the GGUF quantized version of the Microsoft Phi-3-mini-4k-instruct model, using the Q4_K_M quantization level, suitable for efficient operation under the llama.cpp framework. This model is a lightweight but powerful language model, specifically optimized for instruction following tasks.

Natural Language ProcessingGgufMultiple Languages

Imp-v1.5-4B-Phi3 is a high-performance lightweight multimodal large model with only 4 billion parameters, built on the Phi-3 framework and SigLIP visual encoder.

MultimodalTransformers

Gemma is a series of lightweight cutting-edge open-source large language models launched by Google, developed based on the Gemini technology framework, supporting English text generation tasks.

Natural Language ProcessingTransformers

A lightweight text classification model based on the DistilBERT architecture, fine-tuned on the AG News dataset using the TextAttack framework, suitable for news classification tasks.

Natural Language ProcessingTransformers