| language: | |
| - en | |
| - ko | |
| - multilingual | |
| license: apache-2.0 | |
| tags: | |
| - vision, language | |
| - pretrained model | |
| - image-to-text | |
| eos_token: </s> | |
| # veld base | |
| Pretrained Vision Encoder Text Decoder Model in Korean and English. See [Github](https://github.com/AIRC-KETI/veld) for more details. | |
| ## How to use | |
| ```python | |
| from transformers import AutoProcessor, AutoModel | |
| processor = AutoProcessor.from_pretrained("KETI-AIR/veld-base", trust_remote_code=True) | |
| model = AutoModel.from_pretrained("KETI-AIR/veld-base", trust_remote_code=True) | |
| ``` | |
| You can use AutoTokenizer and AutoFeatureExtractor instead AutoProcessor. | |
| You don't need to pass `trust_remote_code=True` for AutoTokenizer and AutoFeatureExtractor | |
| ```python | |
| from transformers import AutoFeatureExtractor, AutoTokenizer, AutoModel | |
| feature_extractor = AutoFeatureExtractor.from_pretrained("KETI-AIR/veld-base") | |
| tokenizer = AutoTokenizer.from_pretrained("KETI-AIR/veld-base") | |
| model = AutoModel.from_pretrained("KETI-AIR/veld-base", trust_remote_code=True) | |
| ``` | |