Vietnamese Image Captioning
Model image captioning tieng Viet duoc train tren Flickr8k va 10k anh MSCOCO da dich sang tieng Viet.
Modellquelle
- Art
- Modell
- Dateigröße
- 913 MB
- Version
- vRevision 62e20f2
- Aktualisiert
- 30. Okt. 2026
- Downloads
- 11
- Quelle
- Hugging Face
Quellenbeschreibung
Vietnamese Image Captioning
Model image captioning tieng Viet duoc train tren Flickr8k va 10k anh MSCOCO da dich sang tieng Viet.
Model nhan mot anh dau vao va sinh mot cau chu thich bang tieng Viet.
Architecture
- Encoder:
facebook/deit-base-distilled-patch16-224 - Decoder:
NlpHUST/gpt2-vietnamese - Transformers class:
VisionEncoderDecoderModel
Usage
from PIL import Image
import torch
from transformers import AutoImageProcessor, AutoTokenizer, VisionEncoderDecoderModel
model_id = "slyviee/vietnamese-image-captioning"
device = "cuda" if torch.cuda.is_available() else "cpu"
tokenizer = AutoTokenizer.from_pretrained(model_id, use_fast=True)
image_processor = AutoImageProcessor.from_pretrained("facebook/deit-base-distilled-patch16-224")
model = VisionEncoderDecoderModel.from_pretrained(model_id).to(device)
model.eval()
image = Image.open("image.jpg").convert("RGB")
pixel_values = image_processor(images=image, return_tensors="pt").pixel_values.to(device)
with torch.no_grad():
output_ids = model.generate(pixel_values, max_new_tokens=40, num_beams=4)
caption = tokenizer.decode(output_ids[0], skip_special_tokens=True)
print(caption)
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Modellartefakte
1 Artefakt
Modellartefakte
1 ArtefaktQuellenauszüge
3 Auszüge
Quellenauszüge
3 Auszüge--- license: apache-2.0 language: - vi pipeline_tag: image-to-text library_name: transformers tags: - image-captioning - vietnamese - vision-encoder-decoder - deit - gpt2 --- # Vietnamese Image Captioning Model image captioning tieng Viet duoc train tren Flickr8k va 10k anh MSCOCO da dich sang tieng Viet. Model nhan mot anh dau vao va sinh mot cau chu thich bang tieng Viet. ## Architecture - Encoder: `facebook/deit-base-distilled-patch16-224` - Decoder: `NlpHUST/gpt2-vietnamese` - Transformers class: `VisionEncoderDecoderModel` ## Usage ```python from PIL import Image import torch from transformers import AutoImageProcessor, AutoTokenizer, VisionEncoderDecoderModel model_id = "slyviee/vietnamese-image-captioning" device = "cuda" if torch.cuda.is_available() else "cpu" tokenizer = AutoTokenizer.from_pretrained(model_id, use_fast=True) image_processor = AutoImageProcessor.from_pretrained("facebook/deit-base-distilled-patch16-224") model = VisionEncoderDecoderModel.from_pretrained(model_id).to(device) model.eval() image = Image.open("image.jpg").convert("RGB") pixel_values = image_processor(images=image, return_tensors="pt").pixel_values.to(device) with torch.no_grad(): output_ids = model.generate(pixel_values, max_new_tokens=40, num_beams=4) caption = tokenizer.decode(output_ids[0], skip_special_tokens=True) print(caption) ```
Source context: 11 downloads · 0 likes · Pipeline image-to-text · Library transformers · Repo slyviee/vietnamese-image-captioning
Source context: 17 downloads · 0 likes · Pipeline image-to-text · Library transformers · Repo slyviee/vietnamese-image-captioning
