Instructions to use procit006/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use procit006/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="procit006/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("procit006/results") model = AutoModelForSequenceClassification.from_pretrained("procit006/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c1e1e84db8c4d333b11171ae0718326f7a1d667f2d396ab1c6c9200f6e1d5e0d
- Size of remote file:
- 5.2 kB
- SHA256:
- 9a9ff9617af115134f3b1e03b0ed4548c66f241feee2b91e3d5ed6b216b74123
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