Instructions to use fredymad/my_awesome_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fredymad/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fredymad/my_awesome_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fredymad/my_awesome_model") model = AutoModelForSequenceClassification.from_pretrained("fredymad/my_awesome_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d6da98cf768ad4036b174643b7b155e709ece3e5467ae1a71925427205ee046a
- Size of remote file:
- 268 MB
- SHA256:
- 44423653e4c012b51a2dc02b968f22938afb97b2c439aa9d1fc1ce8adc907300
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