Instructions to use davidgaofc/training with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davidgaofc/training with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="davidgaofc/training")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("davidgaofc/training") model = AutoModelForSequenceClassification.from_pretrained("davidgaofc/training", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 27ba9b45e135bf5a68cbccf9e817d789d25c676c6a2e0c8d8c5ebecff86f9db5
- Size of remote file:
- 4.66 kB
- SHA256:
- 3218350d392bc2a9b8f25d0d2b431f6befce56a5cbf78f0db7e2958ccf64348d
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