Text Classification
Transformers
PyTorch
English
roberta
distilroberta
sentiment
emotion
twitter
reddit
text-embeddings-inference
Instructions to use michelleli99/emotion_text_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michelleli99/emotion_text_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="michelleli99/emotion_text_classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("michelleli99/emotion_text_classifier") model = AutoModelForSequenceClassification.from_pretrained("michelleli99/emotion_text_classifier", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download training_args.bin from michelleli99/emotion_text_classifier: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/michelleli99/emotion_text_classifier/resolve/refs%2Fpr%2F13/training_args.bin
- Command line
-
hf download hf://michelleli99/emotion_text_classifier@refs/pr/13/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/michelleli99/emotion_text_classifier/resolve/refs%2Fpr%2F13/training_args.bin
3.31 kB
- Xet hash:
- 685b3f6185871342676493e2694a0734ae4c5c054ee7f8dff75888d969f29bc4
- Size of remote file:
- 3.31 kB
- SHA256:
- 543c3b09d3d4e005ccc7c2985ca33c22237345be795f509f25496b30f70054ef
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