Instructions to use A-l-e-x/distilbert-base-uncased-lora-text-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use A-l-e-x/distilbert-base-uncased-lora-text-classification with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("distilbert-base-uncased") model = PeftModel.from_pretrained(base_model, "A-l-e-x/distilbert-base-uncased-lora-text-classification") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from A-l-e-x/distilbert-base-uncased-lora-text-classification: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/A-l-e-x/distilbert-base-uncased-lora-text-classification/resolve/main/training_args.bin
- Command line
-
hf download hf://A-l-e-x/distilbert-base-uncased-lora-text-classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/A-l-e-x/distilbert-base-uncased-lora-text-classification/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- 420a749671bd4befcf49dc03e6e2b9ec916a565424af81101ddb278727f4b9af
- Size of remote file:
- 5.43 kB
- SHA256:
- 6c8b7d9bb9d3f65c4ccb49dc7d763a74b41481f8e435a900589e96c20bdc9766
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