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Hi, thanks for sharing your work and they are great!
Here I have a binary classification task with labels 0 and 1 by embeddings of two sentences, may I ask if should I use SoftmaxLoss for this bina…
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These models are available in live, backtesting & research in the cloud environment.
Access installed models and their revisions
```python
from huggingface_hub import scan_cache_dir
…
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## Computer Vision:
- [x] Add Depth Estimation pipeline
- [ ] Add Image Classification pipeline
- [ ] Add Image Segmentation pipeline
- [ ] Add Mask Generation pipeline
- [ ] Add Object Detecti…
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Let's agree on levels of and tools for manual annotation. Shall I do:
1. topics
2. language identification
3. anonymization (literally, only personal names of private individuals)
4. anything e…
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Hi,
I have tried the original simpletransformers sample code on my local python with the latest simpletransformers version 0.65.1.
I have trained the model using bert model type and "bert-base-unc…
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As specified in this issue: https://github.com/UKPLab/sentence-transformers/issues/350#issuecomment-757687915
The authors of SBERT recommend using CrossEncoders for sentence classification.
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I saw in `sentence_transformers.util` have the `paraphrase_mining` tool that can rank a set of sentences by similarity metric
I would like to fineTune the a paraphraser network into a binary classifi…
khieu updated
3 years ago
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Hi, my task is do sentence pair semantic meaning classification, 0 means the two sentences represent the same meaning, 1 means yes.
For example,
I want to eat breakfast, I need to take my breakfa…
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## 論文リンク
https://arxiv.org/abs/1803.11175
## 公開日(yyyy/mm/dd)
2018/03/29
## 概要
sentence level での embedding として、典型的なベンチマークである Deep Averaging Network (DAN) と Transformer Encoder を使ったモデルを TensorF…
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**Description**
This task involves selection of candidate sentences to annotate followed by manual classification of sentences as having a particular relation or not.