Instructions to use unum-cloud/uform-vl-english with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unum-cloud/uform-vl-english with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="unum-cloud/uform-vl-english")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("unum-cloud/uform-vl-english", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "text_encoder": { | |
| "model_type": "bert", | |
| "dim": 768, | |
| "context_dim": 768, | |
| "vocab_size": 30522, | |
| "padding_idx": 0, | |
| "num_layers": 4, | |
| "num_heads": 12, | |
| "embedding_dim": 256, | |
| "multimodal_layers_ids": [2, 3], | |
| "head_one_neuron": false, | |
| "pooling": "cls", | |
| "max_position_embeddings": 77, | |
| "dropout_prob": 0.1 | |
| }, | |
| "image_encoder": { | |
| "dim": 768, | |
| "patch_size": 16, | |
| "image_size": 224, | |
| "num_layers": 12, | |
| "num_heads": 12, | |
| "embedding_dim": 256, | |
| "pooling": "cls" | |
| } | |
| } |