Instructions to use VeraKrasnobaeva/collocations_processor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use VeraKrasnobaeva/collocations_processor with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("yandex/YandexGPT-5-Lite-8B-instruct") model = PeftModel.from_pretrained(base_model, "VeraKrasnobaeva/collocations_processor") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d3945221410a59420e348dcb63acd8d18b5b802c977a7d8756eafe01079ab1d
- Size of remote file:
- 18 MB
- SHA256:
- 84ec8895809da440553b23360eec17b004ccfc475bf618ff3384a7db42cc35a3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.