Instructions to use nhatminh/jina_4_hard_4_ep with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nhatminh/jina_4_hard_4_ep with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nhatminh/jina_4_hard_4_ep", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("nhatminh/jina_4_hard_4_ep", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff8c1723bcf5308b028f9b134fb08ed4783be7f90ea12ea5d87c3072b2b92ebe
- Size of remote file:
- 17.1 MB
- SHA256:
- b1e0376b0ca081a6b0c18125d251f214835d1165944f9eac39baf8d9cf2b15fe
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