对于这些语言模型/压缩器,其实他们在做的是用自己的预测模式,表示了部分数据先验信息,通过in-context learning,减少在真正进行arithmetic encoding时的编码,这一部分预测模式的大小在实际不应该被考虑的,压缩率仍然符合modeling scaling的法则。在对视频/图像进行编码时,编码解码器的大小只会成为实际部署的瓶颈,
2022-04 PaLM Google PaLM: Scaling Language Modeling with Pathways 2022-04 Chinchilla DeepMind An empirical analysis of compute-optimal large language model training NeurIPS 2022-05 OPT Meta OPT: Open Pre-trained Transformer Language Models 2022-05 UL2 Google Unifying Language Learning Paradigms 20...
(2022). Palm: Scaling language modeling with pathways. arXiv: 2204.02311. Clark, H. H., & Murphy, G. L. (1982). Audience design in meaning and reference, 9, 287–299. Dale, R., & Reiter, E. (1995). Computational interpretations of the gricean maxims in the generation of referring...
Performance Outperformed state-of-the-art in 11 NLP tasks GP7-2 Achieves state-of-the-art results on 7 out of 8 tested language modeling datasets 2%∼15% improvement over BERT Large: 3% improvement over BERT outperforms 2%-20% both BERT and XLNet on GLUE benchmark results Small: perform...
Language modeling is also able to, in principle, learn the tasks of McCann et al. (2018)without the need for explicit supervision of which symbols are the outputs to be pre-dicted.Since the supervised objective is the the same as the unsupervised objective but only evaluated on a subset of...
vocab_size (in args dictionary) from simpletransformers.language_modeling import LanguageModelingModel import logging logging.basicConfig(level=logging.INFO) transformers_logger = logging.getLogger("transformers") transformers_logger.setLevel(logging.WARNING) train_args = { "reprocess_input_data": True, "...
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It doesn't require reward modeling, which makes it more computationally efficient than PPO but slightly worse in terms of quality. Proximal Policy Optimization: Iteratively updates policy to maximize reward while staying close to initial behavior. It uses a reward model to score responses and ...
interest language educators, and can lead to projects centering around various topics (such as art) and activities (such as storytelling). However, a potential drawback is the steep learning curve that 3D modeling software often requires. Read on to discover how generative AI can step in to ...
This is achieved by not storing the attention weights and not computing the key/query scores that are masked due to the causal nature of the language modeling task(这个优化侧重还是理解为一种纯工程化的工作,实际投产中具有不确定性,因为在AI编译器逐渐成为主流计算基础设施,这种手工的优化较大概率会被...