Hugging Face's logo

dumperize
/
movie-picture-captioning

Image-to-Text
Transformers
PyTorch
Russian
vision-encoder-decoder
image-text-to-text
Inference Endpoints
Model card Files Community
1
movie-picture-captioning / README.md
dumperize's picture
dumperize
Update README.md
65e046a
preview code
|
raw
history blame
4.64 kB
metadata
license: apache-2.0
language:
  - ru
metrics:
  - bleu
pipeline_tag: image-to-text
widget:
  - src: >-
      https://huggingface.co/dumperize/movie-picture-captioning/resolve/main/vertical_15x.jpeg
    example_title: Custom Image Sample 1

Model Card for Model ID

This model generate a description for movie posters ... mm, in principle, for any photo.

Model Details

Model Description

This is an encoder decoder model based on VisionEncoderDecoderModel. Google/vit-base-patch16-224-in21k was used as encoder, DeepPavlov/rubert-base-cased as decoder.

We refined the model on the dataset with descriptions and movie posters by russian app Kinoposk. Now the model generates descriptions on the jargon of blockbusters =).

Model Sources

Uses

Direct Use

[More Information Needed]

Out-of-Scope Use

[More Information Needed]

Bias, Risks, and Limitations

[More Information Needed]

Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

Training Details

Training Data

We compiled a dataset from the open source of all Russian-language films for October 2022 - kinopoisk. Films with very short or very long descriptions were not included in the dataset, films with blank or very small images were excluded too.

Preprocessing

The model was trained on 8 16 GB V100 for 90 hours.

Evaluation

Testing Data, Factors & Metrics

Testing Data

[More Information Needed]

Factors

[More Information Needed]

Metrics

[More Information Needed]

Results

[More Information Needed]

Summary

Model Examination [optional]

[More Information Needed]

Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

  • Hardware Type: [More Information Needed]
  • Hours used: [More Information Needed]
  • Cloud Provider: [More Information Needed]
  • Compute Region: [More Information Needed]
  • Carbon Emitted: [More Information Needed]

Technical Specifications [optional]

Model Architecture and Objective

[More Information Needed]

Compute Infrastructure

[More Information Needed]

Hardware

[More Information Needed]

Software

[More Information Needed]

Citation [optional]

BibTeX:

[More Information Needed]

APA:

[More Information Needed]

Glossary [optional]

[More Information Needed]

More Information [optional]

[More Information Needed]

Model Card Authors [optional]

[More Information Needed]

Model Card Contact

[More Information Needed]

How to Get Started with the Model

Use the code below to get started with the model.

Click to expand

[More Information Needed]