Instructions to use yemen2016/memo_positive_ND with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yemen2016/memo_positive_ND with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yemen2016/memo_positive_ND")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yemen2016/memo_positive_ND") model = AutoModelForSequenceClassification.from_pretrained("yemen2016/memo_positive_ND", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b6bb4cdfc21d8b25a69bdef54a7e0b0444eefb19b81386a50d3e895d11603893
- Size of remote file:
- 5.18 kB
- SHA256:
- 35929f71aa50f8a1541b8143fdfaf81dc27e7ccc0f7062a6629233e4b4d07ed9
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