Instructions to use MohitAndSahu/FineTunedModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use MohitAndSahu/FineTunedModel with PEFT:
from peft import PeftModel from transformers import AutoModel base_model = AutoModel.from_pretrained("IDEA-Research/grounding-dino-base") model = PeftModel.from_pretrained(base_model, "MohitAndSahu/FineTunedModel") - Transformers
How to use MohitAndSahu/FineTunedModel with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MohitAndSahu/FineTunedModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from MohitAndSahu/FineTunedModel: direct link, hf CLI and curl.
- Browser
- Download file 26.3 MB
-
https://huggingface.co/MohitAndSahu/FineTunedModel/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://MohitAndSahu/FineTunedModel/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/MohitAndSahu/FineTunedModel/resolve/main/adapter_model.safetensors
26.3 MB
- Xet hash:
- c91bf29a7aed2035f3f27b38043389819a01f301e774a48cbacfae2b6e779248
- Size of remote file:
- 26.3 MB
- SHA256:
- 5be5aba4bd3e7bb00c704e59cd876d9c38833229469db798d9225bb11c4df1cc
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