Instructions to use pcuenq/trainer-chapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pcuenq/trainer-chapter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pcuenq/trainer-chapter")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pcuenq/trainer-chapter") model = AutoModelForSequenceClassification.from_pretrained("pcuenq/trainer-chapter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f6c398736587acb730ebcbef2d40e3688a5518bf8153ff0b9884b5011f72ba67
- Size of remote file:
- 4.03 kB
- SHA256:
- 98b570a68addd696c2977d530efbcf498614a2276a0ada0a92ed619082d69365
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