Instructions to use ChenYanKai2002/OpenPerov-Flash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ChenYanKai2002/OpenPerov-Flash with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.6-27B") model = PeftModel.from_pretrained(base_model, "ChenYanKai2002/OpenPerov-Flash") - Notebooks
- Google Colab
- Kaggle
Download composition.json from ChenYanKai2002/OpenPerov-Flash: direct link, hf CLI and curl.
- Browser
- Download file 713 Bytes
-
https://huggingface.co/ChenYanKai2002/OpenPerov-Flash/resolve/main/composition.json
- Command line
-
hf download hf://ChenYanKai2002/OpenPerov-Flash/composition.json
-
curl -L -o composition.json https://huggingface.co/ChenYanKai2002/OpenPerov-Flash/resolve/main/composition.json
713 Bytes
| { | |
| "model": "OpenPerov Flash", | |
| "artifact": "single combined LoRA adapter", | |
| "method": "rank concatenation; unit coefficient for each stage; no rank truncation", | |
| "rank": 48, | |
| "alpha": 96, | |
| "dtype": "float32", | |
| "tensors": 992, | |
| "bytes": 1400885904, | |
| "sha256": "0cc0706fd2ed78240c492b03ce3112e97dfcc08f935d5976b8375451c0c47067", | |
| "all_input_tensor_blocks_preserved": true, | |
| "probe_count": 12, | |
| "maximum_float64_relative_delta_error": 2.804487023000676e-16, | |
| "checkpoint_numerics": "The additive LoRA updates are preserved. Sequential low-precision full-model merges can have different rounding; this exported adapter has not been re-benchmarked.", | |
| "base_model": "Qwen/Qwen3.6-27B" | |
| } | |