Text Generation
Transformers
Safetensors
English
qwen2
conversational
text-generation-inference
Inference Endpoints

MinPLM-Qwen-200M

paper | code

MiniPLM-Qwen-200M is a 200M model with Qwen achitecture pre-trained from scratch on the Pile using the MiniPLM knowledge distillation framework with the offcial Qwen1.5-1.8B as the teacher model.

We also open-source the pre-training corpus refined by Difference Sampling in MiniPLM for reproducibility.

Evaluation

MiniPLM models achieves better performance given the same computation and scales well across model sizes:

Baseline Models

Citation

@article{miniplm,
    title={MiniPLM: Knowledge Distillation for Pre-Training Language Models}, 
    author={Yuxian Gu and Hao Zhou and Fandong Meng and Jie Zhou and Minlie Huang},
    journal={arXiv preprint arXiv:2410.17215},
    year={2024}
}
Downloads last month
278
Safetensors
Model size
203M params
Tensor type
F32
·
Inference Providers NEW
This model is not currently available via any of the supported third-party Inference Providers, and the model is not deployed on the HF Inference API.

Model tree for MiniLLM/MiniPLM-Qwen-200M

Quantizations
1 model

Datasets used to train MiniLLM/MiniPLM-Qwen-200M

Collection including MiniLLM/MiniPLM-Qwen-200M