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
File size: 368 Bytes
bd8c601 cd51971 bd8c601 cd51971 bd8c601 cd51971 bd8c601 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"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>"
}
|