Text Classification
Transformers
TensorBoard
Safetensors
Polish
xlm-roberta
emotion-classification
roberta
fine-tuned
polish
Eval Results (legacy)
text-embeddings-inference
Instructions to use visegradmedia-emotion/Emotion_RoBERTa_polish6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use visegradmedia-emotion/Emotion_RoBERTa_polish6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="visegradmedia-emotion/Emotion_RoBERTa_polish6")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("visegradmedia-emotion/Emotion_RoBERTa_polish6") model = AutoModelForSequenceClassification.from_pretrained("visegradmedia-emotion/Emotion_RoBERTa_polish6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9df0b734e2685705fc400a9955be6c4d7f51e6c7cd231655eff2963fd88b2995
- Size of remote file:
- 9.67 kB
- SHA256:
- 08d516b1040a2f66c13ec731a8b8d7c810e338d3590998b5240f7d446b2bf876
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