Instructions to use Herb-Lab/LLM_housing_livability with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Herb-Lab/LLM_housing_livability with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="Herb-Lab/LLM_housing_livability")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Herb-Lab/LLM_housing_livability") model = AutoModelForSequenceClassification.from_pretrained("Herb-Lab/LLM_housing_livability", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 16a3475c1f479b110df0c4485151ac728bf4ae5ae9212811949f93469c76f531
- Size of remote file:
- 1.63 GB
- SHA256:
- e1292ee87a0e650308176fb0fa4865ef1fbc16bd8efaa4e820c87672c07e4cd7
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