开源大模型微调和训练-指令遵循语言模型 Alpaca 、GPT-4.0这些大模型越来越强大和智能,但是仍然存在产生虚假信息、传播社会刻板印象和产生有毒语言等许多缺陷,为了能够有效解决这些突出的问题,学术界的参与很重要。但是学术界进行大模型的相关研究很困难,因为许多工业界大模型往往不开源,只提供 API 测试访问。同时,往往缺...
WARNING:root:Loading data... WARNING:root:Formatting inputs... ... WARNING:root:Formatting inputs... WARNING:root:Tokenizing inputs... This may take some time... .. WARNING:root:Tokenizing inputs... This may take some time... Using /home/guodong.li/.cache/torch_extensions/py310_cu11...
python TRL SFTTrainer -在Alpaca上进行llama 2微调-文本字段dataset_text_field（Optional[str]）是训练...
Formatting the array takes time as well. The see the actual throughput rate of your network, transfer a file back and forth several times. Assuming your camera can actually output faster, so that the camera itself isn't the bottleneck, you can try socat to send raw serial data over the T...
add sample sheet formatting for CoT Here's how the website now looks like: default alpaca_eval 2 a6db692 YannDubschanged the title[ENH] alpaca_eval 2.0Jan 3, 2024 YannDubschanged the title[WIP] alpaca_eval 2.0Jan 4, 2024 YannDubsmerged commita023f53intomainJan 10, 2024 ...
Note that, for CoT datasets, we first use thetemplateprovided by FLAN to change the original dataset into various Chain-of-Thoughts forms, and then convert it to the above format. The formatting script can be foundhere. Multi-interface Unified Platform ...
is_randomize_output_order : bool Whether to randomize output_1, output_2 when formatting. batch_size : int Number of examples that will be added in a single prompt. Once you made the evaluator you can also analyze it and add it to the evaluator's leaderboard using the following command...
You can adjust the formatting, size, and opacity with ease so these styles offer plenty to customize. The repeating patterns are pretty easy to setup but I really like the solid line brushes. Those can be used as inking tools or as resources for digital painting. ...
classSupervisedDataset(Dataset):"""Dataset for supervised fine-tuning."""def__init__(self,data_path:str,tokenizer:transformers.PreTrainedTokenizer):super(SupervisedDataset,self).__init__()logging.warning("Loading data...")list_data_dict=utils.jload(data_path)logging.warning("Formatting in...
is_randomize_output_order : bool Whether to randomize output_1, output_2 when formatting. batch_size : int Number of examples that will be added in a single prompt. Once you made the evaluator you can also analyze it and add it to the evaluator's leaderboard using the following command:...