Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Recod/my_awesome_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Recod/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Recod/my_awesome_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Recod/my_awesome_model") model = AutoModelForSequenceClassification.from_pretrained("Recod/my_awesome_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8457e9b30c87a21df28d5e254bd2ecf81357f2bc0fd84129d9329eea3314b1b1
- Size of remote file:
- 5.3 kB
- SHA256:
- ed7db0fa6c021a999eff4e7b2f40c79aebcbae97d080999e72d3d7c697a6e5ca
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