Instructions to use AlanRobotics/bert-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlanRobotics/bert-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AlanRobotics/bert-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AlanRobotics/bert-sentiment") model = AutoModelForSequenceClassification.from_pretrained("AlanRobotics/bert-sentiment") - Notebooks
- Google Colab
- Kaggle
| { | |
| "cls_token": "[CLS]", | |
| "do_basic_tokenize": true, | |
| "do_lower_case": false, | |
| "mask_token": "[MASK]", | |
| "name_or_path": "DeepPavlov/rubert-base-cased", | |
| "never_split": null, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "special_tokens_map_file": "/Users/alanbarsag/.cache/huggingface/hub/models--DeepPavlov--rubert-base-cased/snapshots/4036cab694767a299f2b9e6492909664d9414229/special_tokens_map.json", | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "BertTokenizer", | |
| "unk_token": "[UNK]" | |
| } | |