Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use wjura/lhl-sentiment-analysis-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wjura/lhl-sentiment-analysis-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wjura/lhl-sentiment-analysis-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wjura/lhl-sentiment-analysis-model") model = AutoModelForSequenceClassification.from_pretrained("wjura/lhl-sentiment-analysis-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a13c4da85b2f9e1f79d7ebecd3b47b534c760ec3b0c1d8d85a7d23a2700f93cc
- Size of remote file:
- 268 MB
- SHA256:
- 6cf8ec25a3cf7bcc8e8dd8a21cf2f4193cd357ddb59eef5b130bb082ebf0bdb5
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