Instructions to use dccuchile/albert-tiny-spanish-finetuned-mldoc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dccuchile/albert-tiny-spanish-finetuned-mldoc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dccuchile/albert-tiny-spanish-finetuned-mldoc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dccuchile/albert-tiny-spanish-finetuned-mldoc") model = AutoModelForSequenceClassification.from_pretrained("dccuchile/albert-tiny-spanish-finetuned-mldoc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c23a069f85918331447590f4f18a71628c9503aaf07160b17a3f9993d4d56689
- Size of remote file:
- 21.4 MB
- SHA256:
- 3269b8bd19cf1b225145e4c88e5129ae69ac8d0c5606f5e8ee19885ebe588cf3
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