Abstract: Post-training quantization(PTQ) has been widely studied in recent years because it does not require retraining the network or the entire training dataset. However, naively applying the PTQ ...
Abstract: Quantization is a common method to improve communication efficiency in federated learning (FL) by compressing the gradients that clients upload. Currently, most application scenarios involve ...
Visual instruction tuning towards large language and vision models with GPT-4 level capabilities. Check out the details wth the load_pretrained_model function in ...
The model is pre-trained on 25T tokens using a Warmup Stable Decay learning rate schedule with a batch size of 3072, a peak learning rate of 1e-3 and a minimum learning rate of 1e-5. The NVFP4 ...
conda create -n llava python=3.10 -y conda activate llava pip install --upgrade pip # enable PEP 660 support pip install -e . Check out the details wth the load ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results