Instructions to use avsolatorio/doc-topic-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use avsolatorio/doc-topic-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="avsolatorio/doc-topic-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("avsolatorio/doc-topic-model") model = AutoModelForSequenceClassification.from_pretrained("avsolatorio/doc-topic-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5570505ba8a25fda9fbccd0c0b1789b5f4584f9d2eb50de225225b36c21e3f97
- Size of remote file:
- 568 MB
- SHA256:
- f8627cad5c624f2fb26b4f942ae71819338c569907663ae0a83bfe7382ac3366
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