Instructions to use rbryant19/opscribe-synthesis-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rbryant19/opscribe-synthesis-adapter with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/staging/rhbryant/hf_cache/models--Qwen--Qwen2.5-14B-Instruct/snapshots/cf98f3b3bbb457ad9e2bb7baf9a0125b6b88caa8") model = PeftModel.from_pretrained(base_model, "rbryant19/opscribe-synthesis-adapter") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d3f835122bddb470f53048ff36f1a5116791b8f3a003f9d17b3b03b0b81cc5fe
- Size of remote file:
- 11.4 MB
- SHA256:
- 3fd169731d2cbde95e10bf356d66d5997fd885dd8dbb6fb4684da3f23b2585d8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.