Text Classification
Transformers
PyTorch
Safetensors
Polish
bert
sentiment-analysis
twitter
polish
herbert
Eval Results (legacy)
text-embeddings-inference
Instructions to use bardsai/twitter-sentiment-pl-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bardsai/twitter-sentiment-pl-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bardsai/twitter-sentiment-pl-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bardsai/twitter-sentiment-pl-base") model = AutoModelForSequenceClassification.from_pretrained("bardsai/twitter-sentiment-pl-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dad738c4adfc6c14801e2fd807b8618c67c31502200ff0d0e2816312305d91dc
- Size of remote file:
- 498 MB
- SHA256:
- 2c1d537a9684fe66625e890daa350f51c428027ea36c99e110c64a59e9b4626f
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