Instructions to use boronbrown48/topic_otherTopics_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use boronbrown48/topic_otherTopics_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="boronbrown48/topic_otherTopics_v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("boronbrown48/topic_otherTopics_v1") model = AutoModelForSequenceClassification.from_pretrained("boronbrown48/topic_otherTopics_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dd298f716a5baa0105587b30aba93fdf34dbc57aa6287566ba7d8aa0c0770941
- Size of remote file:
- 2.8 kB
- SHA256:
- d062185d6b584826afedd2a5a292ec41820f163417446bc02d5aaef12876d6ed
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