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:
- 48d3f3526e21bf0375b64144cf71f09cd24367c69f2fb26d4785069d093992b4
- Size of remote file:
- 499 MB
- SHA256:
- 2edc3e642ae062d05c10286af4904aaf11122b347f3504964e318edfe054f2e6
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