Instructions to use Ateeb/EmotionDetector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ateeb/EmotionDetector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ateeb/EmotionDetector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ateeb/EmotionDetector") model = AutoModelForSequenceClassification.from_pretrained("Ateeb/EmotionDetector") - Notebooks
- Google Colab
- Kaggle
| {"do_lower_case": true, "unk_token": "<unk>", "sep_token": "<sep>", "pad_token": "<pad>", "cls_token": "<cls>", "mask_token": "<mask>", "tokenize_chinese_chars": true, "strip_accents": null, "bos_token": "<s>", "eos_token": "</s>", "clean_text": true, "wordpieces_prefix": "##", "model_max_length": 512, "name_or_path": "funnel-transformer/small"} |