Instructions to use cscscsds/ddp_test_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cscscsds/ddp_test_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cscscsds/ddp_test_3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cscscsds/ddp_test_3") model = AutoModelForSequenceClassification.from_pretrained("cscscsds/ddp_test_3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc8ccf9acde4636e90844bec89ff256134d10c462eac844b0d724d98ef65741f
- Size of remote file:
- 511 MB
- SHA256:
- 0994d29384990640f4bfb4ed7e5d39e9a404c9f13c700c120fa9fc3ea509b3e3
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