view(-1) # Enable model parallelism shift_labels = shift_labels.to(shift_logits.device) loss = loss_fct(shift_logits, shift_labels) Tokenizer.attention_mask 作用: tokenizer 为确保 batch input 数据长度一致,会将短句子 pad
Perfumed labels to mask odours from plastics etc. in sealed bagsA laminated, fragrant-smelling composite (1) with a polyolefin-based plastic base film (2) containing a homogeneously dispersed perfume, and a pressure-sensitive layer of adhesive material (3) attached directly to the base film (2...
Closed Description ifromeast STHSF commentedon Apr 12, 2024 STHSF qwen1.5 采用了apply_chat_template()来构造input_ids,对encode之后的input想要修改label不是很方便,可以参考qwen的数据构造的preprocess()代码,我这里简单修改了下,供参考: def preprocess( sources, tokenizer: transformers.PreTrainedTokenizer, ma...
I am wondering why we don't have a `mask` or `mask_img` in SurfaceLabelsMasker here, as we do in NiftiLabelsMasker. Originally posted by @man-shu in #4714 (comment)
Options for numlabel add specifies that numeric values be prefixed to value labels. Value labels that are already numlabeled (using the same mask) are not modified. remove specifies that numeric values be removed from the value labels. If you added numeric values by using a nondefault mask,...
data path包含的是每个患者的原始影像相对于labels.csv文件的路径；mask path包含的是每个患者的感兴趣区...
整合其他一些没有labels的口罩数据集; 主要工作如下: 使用pytorch 版本 yolov5 进行二分类 mask 检测,首次模型训练15天,对数据打标; 数据+标签,人工筛选 打标数据更新数据集再次训练,提升模型精度 二三步骤反复迭代 三次,最终得到 准确率(accuracy)高达 0.995 ,召回率 0.99 的检测模型; ...
2Stock Barcode Mask Label, Red, 2 x 1 in, TCM30-08RE Pricing Formula:$270 setup/order + $0.50/label Artwork Prep:Add $35 (one-time expense) Serial Numbers:Add $0.20/label The custom imprinted barcode mask labels include custom text in black ink. There is no minimum order quantity. ...
MaskCLIP+ trains another segmentation model with pseudo labels extracted from MaskCLIP. Step 0. Download and convert the CLIP models, e.g., mkdir -p pretrain python tools/maskclip_utils/convert_clip_weights.py --model ViT16 # Other options for model: RN50, RN101, RN50x4, RN50x16, RN...
(0), - 'attention_mask': inputs['attention_mask'].squeeze(0), - 'labels': torch.tensor(label, dtype=torch.float) - } - - elif self.prompt_style == 101: - new_dataset = row['new_dataset'] - SOTA = row['SOTA'] - OA = row['OA'] - RQM = round(row['RQM'],1) - - ...