@文心快码valueerror: no codeformer model found 文心快码 出现“ValueError: No CodeFormer model found”错误通常意味着在尝试加载CodeFormer模型时出现了问题。以下是一些可能的解决步骤,你可以按照这些步骤逐一排查问题: 检查CodeFormer模型库的安装: 确保你已经正确安装了CodeFormer模型库
The model uses a Transformer to obtain an embedding vector of the basic block and uses the GNN to update the embedding vector of each basic block of the control flow graph (CFG). Codeformer iteratively executes basic block embedding to learn abundant global information and finally uses the GNN...
在本教程中,您将学习如何在阿里云交互式建模(PAI-DSW)中,基于Wav2Lip、TPS-Motion-Model和CodeFormer技术实现动漫风格的数字人物。 您只需要输入一张动漫形象图片、驱动视频,以及您想让其说的文本内容,它就可以准确地模仿人类的说话动作并将文本内容表达出来。
> python -m torch.distributed.launch --nproc_per_node=8 --master_port=4322 basicsr/train.py -opt options/CodeFormer_stage2.yml --launcher pytorch - Pre-trained CodeFormer of stage II (`codeformer_stage2.pth`) can be found in the folder of Releases v0.1.0: https://github.com/sczhou...
Predict and evaluate FCBFormer on the val split of a dataset: python predictEval.py --train-dataset="[EXPERIMENT NAME]" --data-root="[FULL PATH TO VAL DATASET]" --full-ds=False --pre-split-val=True --model-weights="[FULL PATH TO FOLDER]/Trained models/[EXPERIMENT NAME]/best.pt" ...
MindFormers提供Wikitext2作为预训练数据集,code-alpaca作为微调数据集。 数据集名称适用模型适用阶段下载链接 Wikitext2CodeLlama_34bPretrainLink code-alpacaCodeLlama_34bFinetuneLink HumanEvalCodeLlama_34bEvaluateLink 数据预处理中所用的tokenizer.model可以点击链接进行下载。
(2024.04) [Keyformer] Keyformer: KV Cache reduction through key tokens selection for Efficient Generative Inference(@链接etc) Code unreleased(2023.05) [AutoCompressor] Adapting Language Models to Compress Contextss(@Princeton etc) [AutoCompressor] 222 Stars ...
在本教程中,您将学习如何在阿里云交互式建模(PAI-DSW)中,基于Wav2Lip、TPS-Motion-Model和CodeFormer技术实现动漫风格的数字人物。 您只需要输入一张动漫形象图片、驱动视频,以及您想让其说的文本内容,它就可以准确地模仿人类的说话动作并将文本内容表达出来。
-Pre-trained CodeFormer of stage II (`codeformer_stage2.pth`) can be found in the folder of Releases v0.1.0:https://github.com/sczhou/CodeFormer/releases/tag/v0.1.0 25+ 2426 ###🛸 Stage III - CodeFormer (w=1) 2527 -Training Controllable Module: ...
Predict and evaluate FCBFormer on the val split of a dataset: python predictEval.py --train-dataset="[EXPERIMENT NAME]" --data-root="[FULL PATH TO VAL DATASET]" --full-ds=False --pre-split-val=True --model-weights="[FULL PATH TO FOLDER]/Trained models/[EXPERIMENT NAME]/best.pt" ...