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 flax_model.msgpack from Huntersx/cola_model: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Huntersx/cola_model/resolve/refs%2Fpr%2F1/flax_model.msgpack
- Command line
-
hf download hf://Huntersx/cola_model@refs/pr/1/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/Huntersx/cola_model/resolve/refs%2Fpr%2F1/flax_model.msgpack
438 MB
- Xet hash:
- 5481f58efbdb03647b8f402d33362c5bd21aa2bdb8b556070daccdd7f308d13c
- Size of remote file:
- 438 MB
- SHA256:
- f8fa81c2f9e099a35d1ac33f4a45d68b7a1cc0b20ced7b3fc1599ef3ff6ebd6d
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