Instructions to use SergeyTW/action_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SergeyTW/action_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SergeyTW/action_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SergeyTW/action_model") model = AutoModelForSequenceClassification.from_pretrained("SergeyTW/action_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- feaf56a1edc9047b14311c1e9a0ccf71f86d0c37bf8a675db5ecb9b7df895f05
- Size of remote file:
- 268 MB
- SHA256:
- fe8d7fa3ca7c96b13d5ce2208d07cfb538472aeff719f786f5144d2369889733
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