Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use trnt/twitter_emotions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use trnt/twitter_emotions with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="trnt/twitter_emotions")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("trnt/twitter_emotions") model = AutoModelForSequenceClassification.from_pretrained("trnt/twitter_emotions", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from trnt/twitter_emotions: direct link, hf CLI and curl.
- Browser
- Download file 9.08 MB
-
https://huggingface.co/trnt/twitter_emotions/resolve/refs%2Fpr%2F2/tokenizer.json
- Command line
-
hf download hf://trnt/twitter_emotions@refs/pr/2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/trnt/twitter_emotions/resolve/refs%2Fpr%2F2/tokenizer.json
9.08 MB
File too large to display, you can check the raw version instead.