Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use ninja/video-product-match-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ninja/video-product-match-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ninja/video-product-match-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ninja/video-product-match-classifier") model = AutoModelForSequenceClassification.from_pretrained("ninja/video-product-match-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 223d3bbb5c43c976e8bcbfab2b6d3781af1c6747db471745d22df41106061b98
- Size of remote file:
- 5.14 kB
- SHA256:
- 69dcad2f484eb692da86d1217bc8191cae8a32b6f19daacf611f158e09eb88cd
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