FLAN-T5 is an open-source, sequence-to-sequence, large language model that can be also used commercially. The model was published by Google researchers in late 2022, and has been fine-tuned on multiple tasks. The T5 model reframes various tasks into a text-to-text format, such as translat...
Model: 11B T5-LM 一言以蔽之: Flan你想到的我也想到了! 不过我的指令数据集更丰富多样 T0是紧随Flan发布的论文,和FLan对比有以下以下几个核心差异: 预训练模型差异:Flan是Decoder-only, T0是Encoder-Decoder的T5,并且考虑T5的预训练没有LM目标,因此使用了prompt-tunning中以LM任务继续预训练的T5-LM 指令多样...
python factor_eval.py --model-name huggyllama/llama-7b --early-exit-layers 0,2,4,6,8,10,12,14,32 --data-path /path/to/wiki_factor.csv --output-path output-path.json --num-gpus 1 python factor_eval.py --model-name huggyllama/llama-13b --early-exit-layers 0,2,4,6,8,10,12...
AllenAI:TK-Instruct paper: 2022.4 SUPER-NATURAL INSTRUCTIONS:Generalization via Declarative Instructions on 1600+ NLP Tasks 开源指令集:https://instructions.apps.allenai.org/Model: 11B T5 一言以蔽之:没有最大只有更大的指令集,在英文和非英文的各类任务上超越InstructGPT? Tk-Instruct最大的贡献在于开源了...
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github.com/go-openapi/jsonreference v0.17.0/go.mod h1:g4xxGn04lDIRh0GJb5QlpE3HfopLOL6uZrK/VgnsK9I= github.com/go-openapi/jsonreference v0.19.0/go.mod h1:g4xxGn04lDIRh0GJb5QlpE3HfopLOL6uZrK/VgnsK9I= github.com/go-openapi/jsonreference v0.19.4 h1:3Vw+rh13uq2JFNxgnMTGE1rnoieU9...
Model: 11B T5-LM 一言以蔽之: Flan你想到的我也想到了! 不过我的指令数据集更丰富多样 T0是紧随Flan发布的论文,和FLan对比有以下以下几个核心差异: 预训练模型差异:Flan是Decoder-only, T0是Encoder-Decoder的T5,并且考虑T5的预训练没有LM目标,因此使用了prompt-tunning中以LM任务继续预训练的T5-LM ...
python factor_eval.py --model-name huggyllama/llama-7b --data-path /path/to/wiki_factor.csv --output-path output-path.json --num-gpus 1 python factor_eval.py --model-name huggyllama/llama-13b --data-path /path/to/wiki_factor.csv --output-path output-path.json --num-gpus 2 ...