Hugging Face Overview
Overview
The joaomsimoes/MMW-Assessments model is a 14 billion parameter large language model (LLM) that has been fine-tuned from the robust Qwen/Qwen3-14B base model. This fine-tuning process utilized the TRL (Transformer Reinforcement Learning) library, specifically employing Supervised Fine-Tuning (SFT) to adapt its capabilities.
Key Capabilities
- Text Generation: Capable of generating coherent and contextually relevant text based on given prompts.
- Instruction Following: As a fine-tuned model, it is expected to follow user instructions for various text-based tasks.
- Qwen3 Base: Benefits from the strong foundational capabilities of the Qwen3-14B architecture.
Training Details
The model was trained using the SFT method within the TRL framework. The development environment included:
- TRL: 0.17.0
- Transformers: 4.51.3
- Pytorch: 2.8.0.dev20250319+cu128
- Datasets: 3.6.0
- Tokenizers: 0.21.1
Good For
- General Purpose Text Generation: Suitable for a wide range of applications requiring text output.
- Experimentation: Provides a fine-tuned Qwen3-14B model for further research and development.