Instructions to use CMacD12/my_awesome_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CMacD12/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CMacD12/my_awesome_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CMacD12/my_awesome_model") model = AutoModelForSequenceClassification.from_pretrained("CMacD12/my_awesome_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4b87b6945d569f2b8fb17d3ebe37d57dc85077eec98c5636e52f5c5226ee265e
- Size of remote file:
- 3.96 kB
- SHA256:
- 28e0a91252cf890a9a6c35ae8be21885f3c01cf9312b6fed424d197c1e49c92e
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