Instructions to use young476/genrePredict0601 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use young476/genrePredict0601 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="young476/genrePredict0601")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("young476/genrePredict0601") model = AutoModelForSequenceClassification.from_pretrained("young476/genrePredict0601", device_map="auto") - Notebooks
- Google Colab
- Kaggle
|
Download README.md from young476/genrePredict0601: direct link, hf CLI and curl.
- Browser
- Download file 166 Bytes
-
https://huggingface.co/young476/genrePredict0601/resolve/main/README.md
- Command line
-
hf download hf://young476/genrePredict0601/README.md
-
curl -L -H "Authorization: Bearer $HF_TOKEN" -o README.md https://huggingface.co/young476/genrePredict0601/resolve/main/README.md
166 Bytes
metadata
license: apache-2.0
tags:
- text-classification
library_name: transformers
language:
- ko
base_model:
- skt/kogpt2-base-v2
pipeline_tag: text-classification