Text Classification
Transformers
PyTorch
Safetensors
English
roberta
emotions
multi-class-classification
multi-label-classification
text-embeddings-inference
Instructions to use SamLowe/roberta-base-go_emotions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SamLowe/roberta-base-go_emotions with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SamLowe/roberta-base-go_emotions")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SamLowe/roberta-base-go_emotions") model = AutoModelForSequenceClassification.from_pretrained("SamLowe/roberta-base-go_emotions", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download vocab.json from SamLowe/roberta-base-go_emotions: direct link, hf CLI and curl.
- Browser
- Download file 798 kB
-
https://huggingface.co/SamLowe/roberta-base-go_emotions/resolve/main/vocab.json
- Command line
-
hf download hf://SamLowe/roberta-base-go_emotions/vocab.json
-
curl -L -o vocab.json https://huggingface.co/SamLowe/roberta-base-go_emotions/resolve/main/vocab.json
798 kB
File too large to display, you can check the raw version instead.