Instructions to use emo-nlp/7-emo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emo-nlp/7-emo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="emo-nlp/7-emo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("emo-nlp/7-emo") model = AutoModelForSequenceClassification.from_pretrained("emo-nlp/7-emo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from emo-nlp/7-emo: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
-
https://huggingface.co/emo-nlp/7-emo/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://emo-nlp/7-emo@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/emo-nlp/7-emo/resolve/refs%2Fpr%2F1/tokenizer.json
2.11 MB
File too large to display, you can check the raw version instead.