Instructions to use DRamos/experimental_topic_classification_GPU with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DRamos/experimental_topic_classification_GPU with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DRamos/experimental_topic_classification_GPU")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DRamos/experimental_topic_classification_GPU") model = AutoModelForSequenceClassification.from_pretrained("DRamos/experimental_topic_classification_GPU") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e6148f24b8adc2b025cea4492f10469370edc6f98b6237c4a85ead3c9ec30832
- Size of remote file:
- 3.58 kB
- SHA256:
- 02ba0a4a32b92206dbdc9c6d99ec036838f9050c4d849492052b22f25d5db7f5
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