Instructions to use apus-ailab/APUS-OpenJev-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apus-ailab/APUS-OpenJev-v1 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("apus-ailab/APUS-OpenJev-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download 4B-5949/depth_config.json from apus-ailab/APUS-OpenJev-v1: direct link, hf CLI and curl.
- Browser
- Download file 320 Bytes
-
https://huggingface.co/apus-ailab/APUS-OpenJev-v1/resolve/68e5880df6be3bd820345b9233032e8e325bf4c1/4B-5949/depth_config.json
- Command line
-
hf download hf://apus-ailab/APUS-OpenJev-v1@68e5880df6be3bd820345b9233032e8e325bf4c1/4B-5949/depth_config.json
-
curl -L -o depth_config.json https://huggingface.co/apus-ailab/APUS-OpenJev-v1/resolve/68e5880df6be3bd820345b9233032e8e325bf4c1/4B-5949/depth_config.json
320 Bytes
| { | |
| "prompt_version": "jev.dynamic.prompt.v2", | |
| "exit_depth": 16, | |
| "full_depth": 32, | |
| "model_series": "xDAN-openJet", | |
| "checkpoint_step": 5949, | |
| "source_depth_config_sha256": "6856cf257aa6eeb24dda20702ace04696b5d3db19d647705dedd00cca6f756e6", | |
| "training_mode": "two_exit", | |
| "automatic_routing_validated": false | |
| } | |