Instructions to use stanford-nlpxed/behavior_management_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stanford-nlpxed/behavior_management_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="stanford-nlpxed/behavior_management_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("stanford-nlpxed/behavior_management_model") model = AutoModelForSequenceClassification.from_pretrained("stanford-nlpxed/behavior_management_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from stanford-nlpxed/behavior_management_model: direct link, hf CLI and curl.
- Browser
- Download file 997 MB
-
https://huggingface.co/stanford-nlpxed/behavior_management_model/resolve/main/optimizer.pt
- Command line
-
hf download hf://stanford-nlpxed/behavior_management_model/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/stanford-nlpxed/behavior_management_model/resolve/main/optimizer.pt
997 MB
- Xet hash:
- c82bb7505da395703bad1aa5b802d8f85963f70daac1468d05591d57dd8b02a6
- Size of remote file:
- 997 MB
- SHA256:
- c1ba10985ebf7bad093676dd3ef9b1b77e1eaff6467f262f825761ec71bebea6
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