Instructions to use aarimond/test_ES with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aarimond/test_ES with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aarimond/test_ES")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aarimond/test_ES") model = AutoModelForSequenceClassification.from_pretrained("aarimond/test_ES", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from aarimond/test_ES: direct link, hf CLI and curl.
- Browser
- Download file 670 MB
-
https://huggingface.co/aarimond/test_ES/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://aarimond/test_ES/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/aarimond/test_ES/resolve/main/pytorch_model.bin
670 MB
- Xet hash:
- 026be983dbac4def82f278cd542006b9d635c6f8e6ad09e76630e28c7b8e0700
- Size of remote file:
- 670 MB
- SHA256:
- f2b155f7faa6de919c1d1478f81c54711db453bc6d4380c704f4313eb7f307ab
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