Instructions to use rez-dev/mi-super-modelo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rez-dev/mi-super-modelo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rez-dev/mi-super-modelo")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rez-dev/mi-super-modelo") model = AutoModelForSequenceClassification.from_pretrained("rez-dev/mi-super-modelo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc242173b8604aaa19ea4d1597782d0b68a274040a9b7f065b6cc7bc32a24989
- Size of remote file:
- 47.3 MB
- SHA256:
- f8091a5742672b94ba2ba9193ef41b19c8dcd3dbb0241abdb696c15723858654
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