Text Classification
Transformers
PyTorch
multilingual
English
distilbert
sentiment-analysis
testing
unit tests
Instructions to use dhpollack/distilbert-dummy-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dhpollack/distilbert-dummy-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dhpollack/distilbert-dummy-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dhpollack/distilbert-dummy-sentiment") model = AutoModelForSequenceClassification.from_pretrained("dhpollack/distilbert-dummy-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 263 Bytes
2fd2e4b | 1 | {"do_lower_case": true, "do_basic_tokenize": true, "never_split": null, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512} |