Instructions to use dusersad12/BestCheckpoint-Demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dusersad12/BestCheckpoint-Demo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dusersad12/BestCheckpoint-Demo")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dusersad12/BestCheckpoint-Demo") model = AutoModelForSequenceClassification.from_pretrained("dusersad12/BestCheckpoint-Demo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 763a232a16910858f35951923890c1d4283b0f5a97978c50d096cfcfd74fb94c
- Size of remote file:
- 6 Bytes
- SHA256:
- d3eb539a556352f3f47881d71fb0e5777b2f3e9a4251d283c18c67ce996774b7
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