Instructions to use chc-harvard/tiktok_comment_knowledge_construction_binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chc-harvard/tiktok_comment_knowledge_construction_binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="chc-harvard/tiktok_comment_knowledge_construction_binary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("chc-harvard/tiktok_comment_knowledge_construction_binary") model = AutoModelForSequenceClassification.from_pretrained("chc-harvard/tiktok_comment_knowledge_construction_binary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 724863431d5b03eafaa7e3e55ab2272e34f18409d598c1f8d21f6711178dc6ce
- Size of remote file:
- 438 MB
- SHA256:
- 44741347c97e69bd7ed2b081ba86c4bedecccdde3ac83330a74816d3fc956164
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