Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use ranjitharjun7/Food_Not_Food_Text_Classification_Bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ranjitharjun7/Food_Not_Food_Text_Classification_Bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ranjitharjun7/Food_Not_Food_Text_Classification_Bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ranjitharjun7/Food_Not_Food_Text_Classification_Bert") model = AutoModelForSequenceClassification.from_pretrained("ranjitharjun7/Food_Not_Food_Text_Classification_Bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1dfec80d016e72181b0118d4d4e6392c54de2177c52784207e20992c30753afd
- Size of remote file:
- 5.24 kB
- SHA256:
- bb6b4f046b9e2736a72aa55c7db77145c9143292aa46174f1c704ab0f168b903
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