此外,下游任务的数据和语言模型预训练数据不同,在形式和主题上都可能不同,或者数据随着时间发生改变需要更新。 语言模型需要根据下游任务进行adaption,通过task-specific data或者domain knowledge。 大纲: 为什么要对laguage model进行 adaption。 对语言模型进行adaption的三个阶段:Probing,Fine-tuning,light-weight fine ...
目前对于Domain Adaptation的研究方法主要可分为三类:Model-centric、Data-centric和融合前两者的Hybrid方法。在这篇文章中,作者主要关注了模型架构、特征空间增强、数据选择、预训练技术等问题,简单地融合了Model-centric和Data-centric方法,验证了有效进行域适应的一些策略。总体来讲本文虽然没有提出新颖的复杂模型,但是对...
Exemplary embodiments relate to adapting a generic language model during runtime using domain-specific language model data. The system performs an audio frame-level analysis, to determine if the utterance corresponds to a particular domain and whether the ASR hypothesis needs to be rescored. The ...
Model arguments are arguments that specify which model/tokenizer we are going to train or fine tune. The class below, implements these as adataclass. We will get an instance from this later to pass our choices. The most important field here ismodel_name_or_pathbut for completeness we keep ...
purely via text interaction with the model. GPT-3 achieves strong performance on many NLP datasets, including translation, question-answering, and cloze tasks, as well as several tasks that require on-the-fly reasoning or domain adaptation, such as unscrambling words, using a novel word in a ...
natural-language-processing language-modeling transfer-learning language-model knowledge-transfer continual-learning catastrophic-forgetting transformer-architecture domain-adaptive-pretraining Updated Jan 28, 2024 Python muditbhargava66 / PyxLSTM Star 228 Code Issues Pull requests Discussions Efficient Python...
It’s a time to rejoice in the success of having India’s Large Language Model-based solution-BharatGPT. The solution is a combined effort of CoRover.ai, an AI startup company and the support system ofI-HUB Anubhutidedicated to developing data-driven cognitive computing solut...
Colossal-AI open sources a complete RLHF pipeline that includes supervised data collection, supervised fine-tuning, reward model training, and reinforcement learning fine-tuning, based on the LLaMA pre-trained model, and shares ColossalChat, the most practical open-source project that closely ...
In our experiments, we use the recurrent neural network language model (LM) as a case study. We show that the neural LM perplexity can be reduced by 7.395 and 12.011 using the proposed domain adaptation mechanism on the Penn Treebank and News data, respectively. Furthermore, we show that ...
Meta-learning via Language Model In-context Tuning Evaluating Large Language Models Trained on Code Codex原始论文 Chain-of-Thought Prompting Elicits Reasoning in Large Language CoT原始论文,也从侧面印证,instructGPT从22年1月份之前 就开始迭代了