Instructions to use prxy5605/796390f1-75bb-4f2b-b04d-0cd06bfe4718 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use prxy5605/796390f1-75bb-4f2b-b04d-0cd06bfe4718 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3-mini-128k-instruct") model = PeftModel.from_pretrained(base_model, "prxy5605/796390f1-75bb-4f2b-b04d-0cd06bfe4718") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from prxy5605/796390f1-75bb-4f2b-b04d-0cd06bfe4718: direct link, hf CLI and curl.
- Browser
- Download file 403 MB
-
https://huggingface.co/prxy5605/796390f1-75bb-4f2b-b04d-0cd06bfe4718/resolve/main/adapter_model.bin
- Command line
-
hf download hf://prxy5605/796390f1-75bb-4f2b-b04d-0cd06bfe4718/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/prxy5605/796390f1-75bb-4f2b-b04d-0cd06bfe4718/resolve/main/adapter_model.bin
403 MB
- Xet hash:
- 2ec6dd66e48108bf66084ff3ae2075cb05daf3d46c3ca85bdda5635638e0eb0d
- Size of remote file:
- 403 MB
- SHA256:
- a3d9cebd178084d2c7e07270b4cadf1801208d0435dd1a585ef122c522e38574
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.