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:
- f3fe21b02f593a599fb01cfe4e6dad24ec43a49845a7bea3cb5643b6c1a13c36
- Size of remote file:
- 3.58 kB
- SHA256:
- 94fbe604f17a48bbe37c415e1531fd6705f64f26054df577ed03c279e70cf70b
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