Instructions to use Huntersx/cola_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Huntersx/cola_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Huntersx/cola_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Huntersx/cola_model") model = AutoModelForSequenceClassification.from_pretrained("Huntersx/cola_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Huntersx/cola_model: direct link, hf CLI and curl.
- Browser
- Download file 990 Bytes
-
https://huggingface.co/Huntersx/cola_model/resolve/main/training_args.bin
- Command line
-
hf download hf://Huntersx/cola_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Huntersx/cola_model/resolve/main/training_args.bin
990 Bytes
- Xet hash:
- 9566a6959af1366b6f7b87633c7a3fdcd8ee4c8103c59485ea3a6e5011a2290e
- Size of remote file:
- 990 Bytes
- SHA256:
- 63f7006951a26fc095b0f0f2acf110998bb358efb11cd4cd3e0d04e3ed8f6ee4
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