AAAAnsah/qwen7b_bma_wp_1
AAAAnsah/qwen7b_bma_wp_1 is a 7.6 billion parameter instruction-tuned causal language model, fine-tuned from unsloth/Qwen2.5-7B-Instruct. This model was trained using SFT with the TRL framework, offering a 32K token context length. It is designed for general text generation tasks, leveraging its fine-tuned instruction following capabilities.
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Model Overview
AAAAnsah/qwen7b_bma_wp_1 is a 7.6 billion parameter instruction-tuned language model, building upon the unsloth/Qwen2.5-7B-Instruct base model. It was fine-tuned using Supervised Fine-Tuning (SFT) with the TRL library, a framework for Transformer Reinforcement Learning.
Key Capabilities
- Instruction Following: The model has been fine-tuned to better understand and respond to user instructions, making it suitable for conversational AI and task-oriented generation.
- Text Generation: Capable of generating coherent and contextually relevant text based on prompts.
- Context Length: Supports a substantial context window of 32,768 tokens, allowing for processing and generating longer sequences of text.
Training Details
The model's fine-tuning process utilized the TRL framework (version 0.23.0) alongside Transformers (4.57.6), Pytorch (2.10.0), Datasets (4.3.0), and Tokenizers (0.22.2). This setup indicates a standard and robust training methodology for instruction-tuned models.