Instructions to use DPhO05/my-unixcoder-RQ3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DPhO05/my-unixcoder-RQ3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DPhO05/my-unixcoder-RQ3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DPhO05/my-unixcoder-RQ3") model = AutoModelForSequenceClassification.from_pretrained("DPhO05/my-unixcoder-RQ3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d4d32ee4a159facdf6eecb0527986e7be77c671abf9b364a455dee0977e49eb3
- Size of remote file:
- 5.27 kB
- SHA256:
- 1adebf1b566560828f43dde398b37db0ddbd9c57dad3716c8fcbf8eef26ebf14
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