Text Classification
Transformers
PyTorch
Safetensors
Polish
bert
twitter
emotion
polish
herbert
Eval Results (legacy)
text-embeddings-inference
Instructions to use bardsai/twitter-emotion-pl-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bardsai/twitter-emotion-pl-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bardsai/twitter-emotion-pl-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bardsai/twitter-emotion-pl-base") model = AutoModelForSequenceClassification.from_pretrained("bardsai/twitter-emotion-pl-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "additional_special_tokens": [], | |
| "bos_token": "<s>", | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "<s>", | |
| "do_lowercase_and_remove_accent": false, | |
| "id2lang": null, | |
| "lang2id": null, | |
| "mask_token": "<mask>", | |
| "model_max_length": 512, | |
| "pad_token": "<pad>", | |
| "sep_token": "</s>", | |
| "tokenizer_class": "HerbertTokenizer", | |
| "unk_token": "<unk>" | |
| } | |