Text Classification
Transformers
PyTorch
TensorBoard
English
fnet
Generated from Trainer
Eval Results (legacy)
Instructions to use gchhablani/fnet-large-finetuned-cola-copy2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gchhablani/fnet-large-finetuned-cola-copy2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gchhablani/fnet-large-finetuned-cola-copy2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gchhablani/fnet-large-finetuned-cola-copy2") model = AutoModelForSequenceClassification.from_pretrained("gchhablani/fnet-large-finetuned-cola-copy2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57da60425f880c595089f1af2335150640a2a2559fd619068460b87e106a5397
- Size of remote file:
- 948 MB
- SHA256:
- 514b8775de1704061b4320dba647291f860967bc238118225e6687f40707b3ac
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