Text Classification
Transformers
Safetensors
Chinese
bert
agent
nlp
chinese
sentiment-analysis
emotion
regression
vad
valence-arousal-dominance
macbert
text-embeddings-inference
Instructions to use Pectics/vad-macbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pectics/vad-macbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Pectics/vad-macbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Pectics/vad-macbert") model = AutoModelForSequenceClassification.from_pretrained("Pectics/vad-macbert") - Notebooks
- Google Colab
- Kaggle
Added .lfsconfig
Browse files- .lfsconfig +2 -0
.lfsconfig
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[lfs]
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url = https://huggingface.co/Pectics/vad-macbert.git/info/lfs
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