Instructions to use angelperedo01/proj2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use angelperedo01/proj2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="angelperedo01/proj2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("angelperedo01/proj2") model = AutoModelForSequenceClassification.from_pretrained("angelperedo01/proj2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c1e390dbeec0c9ee9f78a5d4d707be0acdbfd6ceb18d7c8baef55658a2b1aa0
- Size of remote file:
- 738 MB
- SHA256:
- 292344a40a2cb50050861bfc77e0c057c1cde58993dc17b3e023e7e85c820617
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