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Hi @yhcao6 when I run the second step of Open-Vocabulary Detection:`python tools/v3det_ovd_utils/split_base_novel.py datasets/V3Det/annotations/v3det_2023_v1_train.json`, I found this step to do was t…
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I try to use seq2seq in summarization task. In more detail, I have 60k pairs of abstracts and titles and I'm using modified codes from NMT tutorial. I want to improve my results using word2vec embeddi…
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(in reply to https://github.com/gs1/WebVoc/issues/35#issuecomment-982656653 by @mgh128)
Props `gpcCategoryCode, gpcCategoryDescription` have these shortcomings:
- Denormalization. What if two prod…
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options:
* deal better than the `raise Exception` in `detectors.base` in `detect()`
```
🕵️ queue of probes: lmrc.Bullying
/usr/local/lib/python3.10/dist-packages/torch/_utils.py:836: UserWarnin…
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Hello,
I would like to test this promising framework on a similarity classification task. So basically, I have got a dataset with 3 columns: (sentence1,sentence2,label). From what I understand, curre…
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I'm trying to understand this in context of other works in the ecosystem. For example, I'm interested in video. For the video encoder, there is the LoRa tuned and the Fully-finetuned, can I use the em…
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Hello.
I want to fine-tune BERT for Q & A in a different way than the SQuAD mission:
I have pairs of (question, answer)
Part of them are the correct answer (Label - 1)
Part of them are…
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Right now, `skweak` supports two main types of NLP tasks: (token-level) sequence labelling and text classification. Both rests on the idea that labelling functions associate labels to *text spans*, an…
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# Semantic Textual Similarity
## Task Objective
Evaluate the semantic understanding level of the models by comparing with the human-labeled sentence similarity. The task is part of the metatask http…
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# Speech Summary Matching
Speech summarization refers to the process of condensing spoken language into a shorter version while retaining its essential meaning and key points. Speech summarization…