Instructions to use nishhaaann/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nishhaaann/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nishhaaann/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nishhaaann/results") model = AutoModelForSequenceClassification.from_pretrained("nishhaaann/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a6465e28d5b69369aa4b4fbe5d99566cbc967f52c2adab72454d92ef05a43e2
- Size of remote file:
- 541 MB
- SHA256:
- 5130a3a25133a5189b6fb93733ba95fd3c3b4efad12162186b3c9fb48df423e9
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