Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use aephil/lab6-trained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aephil/lab6-trained with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aephil/lab6-trained")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aephil/lab6-trained") model = AutoModelForSequenceClassification.from_pretrained("aephil/lab6-trained", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a60e8a24da14d35dfbd18f585ce7cd3b90f8cfcb594336313ce7706fda8aa49c
- Size of remote file:
- 5.14 kB
- SHA256:
- 8bbc91864ee5b959009c0b4eed2ce54ab0b4c76825519b1fa2e839eea9b814e9
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