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
Download training_args.bin from dccuchile/albert-tiny-spanish-finetuned-mldoc: direct link, hf CLI and curl.
- Browser
- Download file 2.86 kB
-
https://huggingface.co/dccuchile/albert-tiny-spanish-finetuned-mldoc/resolve/main/training_args.bin
- Command line
-
hf download hf://dccuchile/albert-tiny-spanish-finetuned-mldoc/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dccuchile/albert-tiny-spanish-finetuned-mldoc/resolve/main/training_args.bin
2.86 kB
- Xet hash:
- 3e1df683116f9e8fbbe24eb624bf0cbfb5e294dd33dd9a7b592749d39279cd1f
- Size of remote file:
- 2.86 kB
- SHA256:
- b101cb827efbf2428ac696f8952cdeb6a429ee10475c5e291e76cd4327de1e9e
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