Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use TuringGame/distilbert-base-uncased-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TuringGame/distilbert-base-uncased-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TuringGame/distilbert-base-uncased-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TuringGame/distilbert-base-uncased-classifier") model = AutoModelForSequenceClassification.from_pretrained("TuringGame/distilbert-base-uncased-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download .gitattributes from TuringGame/distilbert-base-uncased-classifier: direct link, hf CLI and curl.
- Browser
- Download file 54 Bytes
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https://huggingface.co/TuringGame/distilbert-base-uncased-classifier/resolve/main/.gitattributes
- Command line
-
hf download hf://TuringGame/distilbert-base-uncased-classifier/.gitattributes
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curl -L -o .gitattributes https://huggingface.co/TuringGame/distilbert-base-uncased-classifier/resolve/main/.gitattributes
54 Bytes
| model.safetensors filter=lfs diff=lfs merge=lfs -text | |