Omni-Edu-9B-GGUF

Omni-Edu-9B-GGUF

Omni-Edu-9B is a fine-tuned version of Qwen3.5-9B-Base from OpenDCAI, trained on the Omni-Edu-70K dataset as part of the "OmniEdu: Open Foundation Models for Learning and Teaching" project (arXiv:2609.23088), serving as the larger sibling to Omni-Edu-4B in the same open-foundation-model family targeting educational use cases. Training was conducted via LLaMA-Factory over 3 epochs on 8 GPUs with a learning rate of 5e-6 (cosine schedule, 10% warmup), a total effective batch size of 64, and the fused AdamW optimizer, using Transformers 5.2.0 and PyTorch 2.10.0. The model card itself is auto-generated and sparse — model description, intended uses/limitations, and detailed training/evaluation results are not yet documented in the repository, so specifics on capabilities and benchmark performance should be sought in the accompanying paper; it is released under a custom "other" license rather than a standard open license.

Model Files

llama.cpp

LLM inference in C/C++ — https://github.com/ggml-org/llama.cpp