Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
distilbert
text-embeddings-inference
Instructions to use ebrigham/EYY-Topic-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ebrigham/EYY-Topic-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ebrigham/EYY-Topic-Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ebrigham/EYY-Topic-Classification") model = AutoModelForSequenceClassification.from_pretrained("ebrigham/EYY-Topic-Classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f732852f472184b7d578012ddc519c1b286a399d7883c0013d7249f40f11d0e0
- Size of remote file:
- 2.99 kB
- SHA256:
- 736ff2f74ff7a20eb7c6ec947c546081d7c85fdea93f26ed28c58421d13dcae5
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