Instructions to use UCSC-VLAA/openvision2-vit-huge-patch14-448-vision-only with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- OpenCLIP
How to use UCSC-VLAA/openvision2-vit-huge-patch14-448-vision-only with OpenCLIP:
import open_clip model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms('hf-hub:UCSC-VLAA/openvision2-vit-huge-patch14-448-vision-only') tokenizer = open_clip.get_tokenizer('hf-hub:UCSC-VLAA/openvision2-vit-huge-patch14-448-vision-only') - Notebooks
- Google Colab
- Kaggle
| { | |
| "architecture": "OpenVision2TextDecoder", | |
| "fusion_style": "concat", | |
| "width": 1024, | |
| "depth": 24, | |
| "num_heads": 16, | |
| "mlp_dim": 4096, | |
| "vocab_size": 32000, | |
| "vision_width": 1280, | |
| "layer_norm_eps": 1e-06, | |
| "pad_id": 0, | |
| "bos_id": 1, | |
| "eos_id": 2, | |
| "weights_file": "caption_decoder.safetensors", | |
| "modeling_file": "modeling_openvision2_decoder.py", | |
| "tokenizer": "bert wordpiece (bert_base_vocab_bos_eos.txt), lowercase, [PAD]=0 [bos]=1 [eos]=2" | |
| } |