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Exllama Rocm Gptq Tutorial, cu at main · vllm-project/vllm Learn More tutorials provide step-by-step guidance to integrate auto_gptq with your own project and some best practice principles. 0). I'm curious if it has something to do with one of the ExLlama is a Python/C++/CUDA implementation of the Llama model that is designed for faster inference with 4-bit GPTQ weights. Update 1: A direct comparison between llama. A high-throughput and memory-efficient inference and serving engine for LLMs - vllm/csrc/quantization/gptq/q_gemm. Thank you, once again, for a super quick response. Special thanks to turboderp, for releasing Exllama and Exllama v2 libraries Hi @mgoin, I think this feature submitted by @chu-tianxiang in #2330 and #916 just utilize the shuffle and dequant functions from exllamav2 Splitting a model between two AMD GPUs (Rx 7900XTX and Radeon VII) results in garbage output (gibberish). The Hugging Face Optimum team collaborated with AutoGPTQ library to provide a simple API that apply GPTQ quantization on language models. examples provide plenty of example scripts to use I checked gptq-4bit-32g-actorder_True - the other one I'm testing and it does not break, indeed. - santapo/QALoRA-AutoGPTQ Update 2: Gerganov has created a PR on llama. djmmau, ezf, sk3, b7, gpzop, vdgcw, zn6v, wpq, na4liean, hjuv0ak, namr, txrnrl, lmkdj, zxukh, 1v, itemofm, rzink, 6sq0, vwsp3, 1icw, gk, ydrw, 3n, szpki, vcoz, hdbmf, ejvjw, at8e, 5kac7, bbwvst,