Instructions to use Jillian/results_tinybert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jillian/results_tinybert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jillian/results_tinybert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jillian/results_tinybert") model = AutoModelForSequenceClassification.from_pretrained("Jillian/results_tinybert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Jillian/results_tinybert: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/Jillian/results_tinybert/resolve/main/training_args.bin
- Command line
-
hf download hf://Jillian/results_tinybert/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Jillian/results_tinybert/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- 9d996c20d6e2e796645d78d41d2d3ee91dbb8c3e13ca184c63d42a026510ff6b
- Size of remote file:
- 5.37 kB
- SHA256:
- 9f18dbb661b33ef53aa9729ac3c90da3e0b811a83f2d54085432f4a4a3f5d07f
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