tokenizer, prompt) dash_line = '-'*100 print(dash_line) print(f'Input Prompt:\n{prompt}') print(dash_line) print(f'Human Summary:\n{summary}') print(dash_line) print(f'Full fine-tuning Model Summary:\n{output}')
> /workspace/asr/peft/examples/causal_language_modeling/peft_prompt_tuning_clm.py(178)<module>() 177 # creating model --> 178 model = AutoModelForCausalLM.from_pretrained(model_name_or_path) 179 model = get_peft_model(model, peft_config) 得到的模型为: ipdb> model BloomForCausalLM( (...
Although we'll focus on the causal language modeling task here, the PEFT library supports various tasks, models, and tuning techniques. You can find compatible PEFT methods for other models and tasks on the PEFT documentation page. 1. Loading model and tokenizer To start, we load the model ...
- [Fine-Tuning Models using Prompt-Tuning with Hugging Face’s PEFT Library](https://pub.towardsai.net/fine-tuning-models-using-prompt-tuning-with-hugging-faces-peft-library-998ae361ee27). This seems very similar to the LoRA fine-tuning. - [Prompt tuning for causal language modeling, offici...
🎉LLMs Usage Guide🎉: The method for quickly getting started with large language models by using LangChain. In the future, there will likely be two types of people on Earth (perhaps even on Mars, but that's a question for Musk): ...
PEKD: Joint Prompt-Tuning andEnsemble Knowledge Distillation Framework forCausal Event Detection fromBiomedical Literaturedoi:10.1007/978-981-97-0837-6_10Identifying causal precedence relations among chemical interactions in biomedical literature is crucial for comprehending the underlying biological mechanisms....
Prompt-MolOpt is a tool for molecular optimization; it makes use of prompt-based embeddings, as used in large language models, to improve the transformer’s ability to optimize molecules for specific property adjustments. Notably, Prompt-MolOpt excels in working with limited multiproperty data (...
Recently, prompt tuning has been widely applied to stimulate the rich knowledge in pre-trained language models (PLMs) to serve NLP tasks. Although prompt tuning has achieved promising results on some few-class classification tasks, such as sentiment classification and natural language inference, manual...
Causal-Debias: Unifying Debiasing in Pretrained Language Models and Fine-tuning via Causal Invariant Learning Demographic biases and social stereotypes are common in pretrained language models (PLMs), and a burgeoning body of literature focuses on removing the unwa... F Zhou,Y Mao,L Yu,... 被引...
Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoning 大语言模型可以通过溯因推理来提升事件预测性能 本文由蚂蚁集团、芝加哥大学和芝加哥丰田工业大学合作完成 文章作者：师晓明、薛思乔、王康瑞 周 凡、James Y. Zhang 周 俊、谭宸浩、梅洪源 论文链接：https://openreview.net/forum?id=...