Instructions to use zeromodels/tipsv2-g14-dpt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasFormers
How to use zeromodels/tipsv2-g14-dpt with KerasFormers:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Keras
How to use zeromodels/tipsv2-g14-dpt with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://zeromodels/tipsv2-g14-dpt") - Notebooks
- Google Colab
- Kaggle
| { | |
| "library_name": "kerasformers", | |
| "kerasformers_version": "1.2.5", | |
| "model_module": "kerasformers.models.tipsv2_dpt", | |
| "model_class": "Tipsv2DptDensePredict", | |
| "variant": "tipsv2-g14-dpt", | |
| "weights": "model.weights.h5", | |
| "schema_version": 2, | |
| "model_type": "tipsv2_dpt", | |
| "vision_config": { | |
| "image_size": 448, | |
| "patch_size": 14, | |
| "num_register_tokens": 1, | |
| "vision_hidden_dim": 1536, | |
| "vision_num_layers": 40, | |
| "vision_num_heads": 24, | |
| "vision_mlp_ratio": 4, | |
| "vision_use_swiglu_ffn": true, | |
| "vision_layerscale_value": 1.0, | |
| "vision_layer_norm_eps": 1e-06, | |
| "out_indices": [ | |
| 10, | |
| 20, | |
| 30, | |
| 40 | |
| ], | |
| "neck_hidden_sizes": [ | |
| 192, | |
| 384, | |
| 768, | |
| 1536 | |
| ], | |
| "reassemble_factors": [ | |
| 4, | |
| 2, | |
| 1, | |
| 0.5 | |
| ], | |
| "fusion_hidden_size": 256, | |
| "readout_activation": "gelu_tanh", | |
| "num_depth_bins": 256, | |
| "min_depth": 0.001, | |
| "max_depth": 10.0, | |
| "depth_decoder_activation": "relu", | |
| "num_labels": 150 | |
| } | |
| } |