Reasonablellama3 3B Jr
LLaMA-3Bを基に構築された微調整推論モデル、推論能力を強化し、多言語処理をサポート
ダウンロード数 1,173
リリース時間 : 3/4/2025
モデル概要
ReasonableLlama-3BはLLaMA-3Bを基に構築された推論モデルで、微調整により推論能力が強化され、多様な言語処理タスクをサポートします。
モデル特徴
多言語サポート
英語、ドイツ語、フランス語など8言語のテキスト生成と推論をサポート
強化された推論能力
特別な微調整により、モデルの論理的推論と連鎖思考能力が向上
エッジデバイス対応
小型LLMとして、エッジデバイスでの展開と実行に適している
モデル能力
多言語テキスト生成
論理的推論
連鎖思考
命令追従
使用事例
教育
言語学習支援
学習者が多言語でのライティングと読解を練習するのを支援
研究
小型LLM研究
エッジコンピューティングシナリオにおける小型言語モデルの性能研究に使用
tags:
- meta
- pytorch
- llama
- llama-3
- mlx
- mlx
- reasoning
- llama
- deepseek
- ollama
- chain-of-thoughts
- small-llm
- edge base_model: mlx-community/Llama-3.2-3B-Instruct language:
- en
- de
- fr
- it
- pt
- hi
- es
- th
library_name: transformers
license: llama3.2
pipeline_tag: text-generation
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ReasonableLlama-3B: A Fine-Tuned Reasoning Model
HF: https://huggingface.co/adeelahmad/ReasonableLlama3-3B-Jr Ollama: https://ollama.com/adeelahmad/ReasonableLLAMA-Jr-3b
Welcome to ReasonableLlama-3B, a cutting-edge reasoning model built on the foundation of LLaMA-3B. This model has been carefully fine-tuned to enhance its capabilities in logical thinking, problem-solving, and creative analysis.
Overview
- Model Name: ReasonableLlama-3B
- Base Architecture: LLaMA-3B (Large Language Model with 3B parameters)
- Purpose: Designed for tasks requiring advanced reasoning, problem-solving, and creative thinking
Features
- Advanced Reasoning: Excels in logical analysis, problem-solving, and decision-making.
- Creative Thinking: Generates innovative solutions and ideas.
- Curriculum-Based Fine-Tuning: Trained on high-quality datasets to enhance reasoning abilities.
Technical Details
- Parameter Count: 3B parameters
- Training Process: Fine-tuned using state-of-the-art techniques for reasoning tasks
- Specialization: Optimized for specific reasoning workflows and scenarios
Use Cases
- Research: Facilitates complex problem-solving and theoretical analysis.
- Education: Assists in creating educational examples and problem sets.
- Problem Solving: Helps generate innovative solutions across various domains.
Installation and Usage
- Integration: Can be integrated into existing systems via APIs or local setup.
- Inputs: Supports text and images, leveraging Ollama's versatile capabilities.
Limitations
- Scope: Limited to single-step reasoning; multi-hop reasoning is a current focus area.
- Data Bias: Caution with dataset provenance as it may reflect historical biases.
Contributing
Contributions welcome! Fork the project, submit issues, and pull requests on GitHub. Your insights can help shape future improvements.
Citations
- Special thanks to LLaMA's developers for providing a strong foundation.
- Acknowledgments to the community contributing to open-source AI advancements.
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