Instructions to use ElMad/likeable-donkey-705 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ElMad/likeable-donkey-705 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ElMad/likeable-donkey-705")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ElMad/likeable-donkey-705") model = AutoModelForSequenceClassification.from_pretrained("ElMad/likeable-donkey-705", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ElMad/likeable-donkey-705: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/ElMad/likeable-donkey-705/resolve/main/training_args.bin
- Command line
-
hf download hf://ElMad/likeable-donkey-705/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ElMad/likeable-donkey-705/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- eefc74d9b033e3404bc966c1ec27a9cc7a9033e8b0f1433be906b8c661168a30
- Size of remote file:
- 5.43 kB
- SHA256:
- 0fb62ffa477dada13e658d3bb0e80edb0b0c5eec317371663e755df18579758c
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