Instructions to use AndreiUrsu/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AndreiUrsu/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AndreiUrsu/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AndreiUrsu/results") model = AutoModelForSequenceClassification.from_pretrained("AndreiUrsu/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ed647e0afa7c6825c17702ef8257ab8284bf42103339c35a5394764a5ca1f0c
- Size of remote file:
- 4.98 kB
- SHA256:
- 66aeca8c6c011406e3fd3da41900956b7825782c163f3ae31988a396fbd8cc2f
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