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:
- 208188b27a43ffe991829407e728bc7740c9771e311db41d909a08c91b852ff1
- Size of remote file:
- 4.96 GB
- SHA256:
- a53cdfbbe35d39d032d434194291b8388073c26d31e5b8ed355f33c1e0cb039e
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