Instructions to use lancehar/last_linear_seed5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lancehar/last_linear_seed5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lancehar/last_linear_seed5", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("lancehar/last_linear_seed5", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 22c82a0bb9bf1324774e3eeff63df77e6a9959d9f2dd5de8e7365e62ea375c30
- Size of remote file:
- 115 MB
- SHA256:
- 5d28aa3557890cbfdba4ee9e8a97afed4c30318c99a18f6b0cb0cffd0319483b
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