Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use yeye776/DistilKoBERT-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yeye776/DistilKoBERT-ft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yeye776/DistilKoBERT-ft")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yeye776/DistilKoBERT-ft") model = AutoModelForSequenceClassification.from_pretrained("yeye776/DistilKoBERT-ft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from yeye776/DistilKoBERT-ft: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
-
https://huggingface.co/yeye776/DistilKoBERT-ft/resolve/main/training_args.bin
- Command line
-
hf download hf://yeye776/DistilKoBERT-ft/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/yeye776/DistilKoBERT-ft/resolve/main/training_args.bin
5.05 kB
- Xet hash:
- 52c6bf498aac875261d7628aad008214b11ba8338ed9c87dac3e21aeaf75d09c
- Size of remote file:
- 5.05 kB
- SHA256:
- 7a36e794b76063c3600df3cb609d5412bf496a349d4f0be875da1576d7e0cd16
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.