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")# pip install -U transformers accelerate # 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
Download tokenizer.json from bardsai/twitter-sentiment-pl-base: direct link, hf CLI and curl.
- Browser
- Download file 2.3 MB
-
https://huggingface.co/bardsai/twitter-sentiment-pl-base/resolve/main/tokenizer.json
- Command line
-
hf download hf://bardsai/twitter-sentiment-pl-base/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/bardsai/twitter-sentiment-pl-base/resolve/main/tokenizer.json
2.3 MB
File too large to display, you can check the raw version instead.