Search results
bitnet.cpp is the official inference framework for 1-bit LLMs (e.g., BitNet b1.58). It offers a suite of optimized kernels, that support fast and lossless inference of 1.58-bit models on CPU (with NPU and GPU support coming next).
bitnet.cpp is the official inference framework for 1-bit LLMs (e.g., BitNet b1.58). It offers a suite of optimized kernels, that support fast and lossless inference of 1.58-bit models on CPU (with NPU and GPU support coming next).
28 lut 2024 · Recent research, such as BitNet, is paving the way for a new era of 1-bit Large Language Models (LLMs). In this work, we introduce a 1-bit LLM variant, namely BitNet b1.58, in which every single parameter (or weight) of the LLM is ternary {-1, 0, 1}.
11 mar 2024 · Existing Quantization Approaches Vs BitNet 1.58bit. Most quantization algorithms present in the market requires a pretrained model in full precision. And one would apply techniques such as Post Training Quantization and Quantization Aware Training for such algorithms to work effectively.
5 sie 2024 · In recent developments, the BitNet b1.58 architecture has shown remarkable adaptability and efficiency, even when scaled down for smaller networks. This breakthrough addresses the growing need...
29 mar 2024 · Here is the commands to run the evaluation: pip install lm-eval==0.3.0. python eval_ppl.py --hf_path 1bitLLM/bitnet_b1_58-3B --seqlen 2048. python eval_task.py --hf_path 1bitLLM/bitnet_b1_58-3B \ --batch_size 1 \ --tasks \ --output_path result.json \ --num_fewshot 0 \ --ctx_size 2048.
29 lut 2024 · BitNet b1.58 emerges as a solution, utilizing 1-bit ternary parameters to dramatically lighten the load on computational resources while maintaining high model performance. This section...
