Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use anth0nyhak1m/SS_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anth0nyhak1m/SS_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anth0nyhak1m/SS_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anth0nyhak1m/SS_model") model = AutoModelForSequenceClassification.from_pretrained("anth0nyhak1m/SS_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 354d4fcc1f478a26fc826adb59df4e77b43b8e31ad1475137e6aa0191aef40c7
- Size of remote file:
- 3.58 kB
- SHA256:
- 0e1dde0235a286a7026dce787c4d38bccb6f73cf88bd43e30dda9ff82e3641fa
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