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Nlpconnect

Rank:

Average Model Cost: $0.0000

Number of Runs: 1,290,748

Models by this creator

📊

vit-gpt2-image-captioning

The "vit-gpt2-image-captioning" model is an image-to-text model that generates captions for given images. It uses the Vision Transformer (ViT) model as the image encoder and the GPT-2 model as the text decoder. By combining these two models, it is able to effectively understand the visual content of the images and generate accurate and coherent captions for them.

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$-/run

1.3M

Huggingface

🔍

roberta-base-squad2-nq

Platform did not provide a description for this model.

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$-/run

4.2K

Huggingface

🔍

deberta-v3-xsmall-squad2

No description available.

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$-/run

126

Huggingface

🧠

dpr-ctx_encoder_bert_uncased_L-2_H-128_A-2

This model(google/bert_uncased_L-2_H-128_A-2) was trained from scratch on training data: data.retriever.nq-adv-hn-train(facebookresearch/DPR). It achieves the following results on the evaluation set: evaluation dataset: facebook-dpr-dev-dataset from official DPR github evaluation dataset: UKPLab/beir test data but we have used first 2lac passage only. Note: * means we have evaluated on same eval dataset. The following hyperparameters were used during training:

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$-/run

70

Huggingface

🗣️

dpr-question_encoder_bert_uncased_L-2_H-128_A-2

Platform did not provide a description for this model.

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$-/run

63

Huggingface

🎲

dpr-nq-reader-roberta-base

Platform did not provide a description for this model.

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$-/run

20

Huggingface

🐍

dpr-nq-reader-roberta-base-v2

Platform did not provide a description for this model.

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$-/run

13

Huggingface

🤔

distilbert-base-cased-wikiproperties-classifier

Platform did not provide a description for this model.

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$-/run

12

Huggingface

🎲

PubLayNet-faster_rcnn_R_50_FPN_3x

Platform did not provide a description for this model.

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$-/run

0

Huggingface

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