Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use kitsunea/distilbert-assignment1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kitsunea/distilbert-assignment1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kitsunea/distilbert-assignment1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kitsunea/distilbert-assignment1") model = AutoModelForSequenceClassification.from_pretrained("kitsunea/distilbert-assignment1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d7660c541dd348b2ef83a4d7f34fad21238d16d03dcd00f799b5199c616006a4
- Size of remote file:
- 5.78 kB
- SHA256:
- 59a30765e237d29adbfa0ad8386c25008557a28d74f946e24a3fbcead659829f
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