Instructions to use HAO-K/powerinfer-seq-cls with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HAO-K/powerinfer-seq-cls with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HAO-K/powerinfer-seq-cls")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HAO-K/powerinfer-seq-cls") model = AutoModelForSequenceClassification.from_pretrained("HAO-K/powerinfer-seq-cls", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e74458f3c8605a2b2d3494d01ed91a70752774105b684d01f66e073bbe4b34e3
- Size of remote file:
- 1.21 GB
- SHA256:
- 77fc885329ae15340aefba8e310b181b72ec27f4820fae3f3ea82ef2f7720ad2
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