Instructions to use m2af/klue-roberta-large-detail_emotion-classifier-basic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m2af/klue-roberta-large-detail_emotion-classifier-basic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="m2af/klue-roberta-large-detail_emotion-classifier-basic")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("m2af/klue-roberta-large-detail_emotion-classifier-basic") model = AutoModelForSequenceClassification.from_pretrained("m2af/klue-roberta-large-detail_emotion-classifier-basic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from m2af/klue-roberta-large-detail_emotion-classifier-basic: direct link, hf CLI and curl.
- Browser
- Download file 1.35 GB
-
https://huggingface.co/m2af/klue-roberta-large-detail_emotion-classifier-basic/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://m2af/klue-roberta-large-detail_emotion-classifier-basic/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/m2af/klue-roberta-large-detail_emotion-classifier-basic/resolve/main/pytorch_model.bin
1.35 GB
- Xet hash:
- 67af578325f3ca1c396b74d7c63be303dc9b00cf6e0202c85880d503c2bb935d
- Size of remote file:
- 1.35 GB
- SHA256:
- d163d9abd7bc16b8208d9d98f064f1f328c3dae6df06c545e8fca66d1259633c
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