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
Commit History
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docs: add CC BY 4.0 license (inherited from HerBERT) and restructure model card per HF guidelines
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (b2be5f23bbe25cc74ddab851443991121335f6ea) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>e05cce1
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