yasserrmd/Human-Like-Qwen2.5-1.5B-Instruct

TEXT GENERATIONConcurrency Cost:1Model Size:1.5BQuant:BF16Ctx Length:32kTool Calling:SupportedPublished:Jan 16, 2025License:otherArchitecture:Transformer Cold

The yasserrmd/Human-Like-Qwen2.5-1.5B-Instruct is a 1.5 billion parameter instruction-tuned causal language model based on the Qwen2.5 architecture, developed by yasserrmd. Fine-tuned using the HumanLLMs/Human-Like-DPO-Dataset, this model is designed to generate human-like responses across a wide range of conversational prompts. It supports a 32768 token context length and is suitable for applications requiring natural language interaction in multiple languages.

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Model Overview

The yasserrmd/Human-Like-Qwen2.5-1.5B-Instruct is a 1.5 billion parameter instruction-tuned language model built upon the Qwen2.5 architecture. This model was specifically trained using AutoTrain and fine-tuned with the HumanLLMs/Human-Like-DPO-Dataset, aiming to enhance its ability to produce responses that mimic human conversation patterns.

Key Capabilities

  • Human-Like Interaction: Optimized for generating natural and conversational text, making it suitable for dialogue systems and interactive applications.
  • Multilingual Support: The model is designed to handle inputs and generate outputs in a variety of languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, and Arabic.
  • Instruction Following: As an instruction-tuned model, it is capable of understanding and executing user prompts effectively.
  • Extended Context Window: Features a substantial context length of 32768 tokens, allowing for processing and generating longer, more coherent interactions.

Good For

  • Chatbots and Conversational AI: Its human-like response generation makes it ideal for customer service bots, virtual assistants, and interactive storytelling.
  • Multilingual Applications: Suitable for global applications requiring natural language processing across diverse linguistic backgrounds.
  • Prototyping and Development: A 1.5B parameter model offers a balance between performance and computational efficiency, making it accessible for various development environments.

Finetunes
2 models