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/merge-provenance.json from apus-ailab/APUS-OpenJev-v1: direct link, hf CLI and curl.
- Browser
- Download file 682 Bytes
-
https://huggingface.co/apus-ailab/APUS-OpenJev-v1/resolve/dbb25630720f247b0054ec9f261593d8aa4e0e98/4B-5949/merge-provenance.json
- Command line
-
hf download hf://apus-ailab/APUS-OpenJev-v1@dbb25630720f247b0054ec9f261593d8aa4e0e98/4B-5949/merge-provenance.json
-
curl -L -o merge-provenance.json https://huggingface.co/apus-ailab/APUS-OpenJev-v1/resolve/dbb25630720f247b0054ec9f261593d8aa4e0e98/4B-5949/merge-provenance.json
682 Bytes
| { | |
| "base_id": "Qwen/Qwen3.5-4B", | |
| "base_revision": "851bf6e806efd8d0a36b00ddf55e13ccb7b8cd0a", | |
| "checkpoint_step": 5949, | |
| "adapter_sha256": "71154f60ec72c55d2c6c6147b9cdda9cc9a52d46297f3074dded7cdc9f5bc344", | |
| "adapter_config_sha256": "c6caee3818ca1f6c8539e47fac9b9fa818d28b61a4bbb05f6f8444c0dd639e45", | |
| "official80_sha256": "b3374e82f0e605762d40ab6455449c9cb2d315804a175d1cda985cba9beded35", | |
| "software": { | |
| "torch": "2.8.0+cu128", | |
| "transformers": "5.16.1", | |
| "peft": "0.20.0" | |
| }, | |
| "merge_arithmetic": "float32 CPU safe_merge then bfloat16 storage", | |
| "inference_dtype": "bfloat16", | |
| "attention": "sdpa", | |
| "gpu": "NVIDIA RTX PRO 6000 Blackwell Server Edition" | |
| } | |