Instructions to use pseudo2010/my_awesome_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pseudo2010/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pseudo2010/my_awesome_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pseudo2010/my_awesome_model") model = AutoModelForSequenceClassification.from_pretrained("pseudo2010/my_awesome_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 41b2c6c6ba01be29e48b229e179956c3ae783ab7e75b6a1831a64f227cfe029e
- Size of remote file:
- 268 MB
- SHA256:
- 85d67919cda196de488cce9e6dd486f025180d4aab08165aae84a9d1cceef8a7
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