nomeda-lab/Fattah-Orch-Medium
Fattah-Orch-Medium is a 4 billion parameter Qwen3-based causal language model developed by nomeda-lab. This model was finetuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general language tasks, leveraging its efficient training methodology.
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nomeda-lab/Fattah-Orch-Medium Overview
Fattah-Orch-Medium is a 4 billion parameter language model developed by nomeda-lab. It is based on the Qwen3 architecture and was finetuned from unsloth/qwen3-4b-unsloth-bnb-4bit.
Key Characteristics
- Architecture: Qwen3-based causal language model.
- Parameter Count: 4 billion parameters.
- Training Efficiency: Finetuned using Unsloth and Huggingface's TRL library, which facilitated 2x faster training compared to standard methods.
- Context Length: Supports a context length of 32768 tokens.
Intended Use Cases
This model is suitable for a variety of general language generation and understanding tasks, benefiting from its efficient finetuning process. Its Qwen3 foundation and substantial context window make it adaptable for applications requiring robust language capabilities.