Text Classification
Transformers
PyTorch
English
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use henryscheible/cola with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use henryscheible/cola with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="henryscheible/cola")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("henryscheible/cola") model = AutoModelForSequenceClassification.from_pretrained("henryscheible/cola", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download eval_results.json from henryscheible/cola: direct link, hf CLI and curl.
- Browser
- Download file 239 Bytes
-
https://huggingface.co/henryscheible/cola/resolve/main/eval_results.json
- Command line
-
hf download hf://henryscheible/cola/eval_results.json
-
curl -L -o eval_results.json https://huggingface.co/henryscheible/cola/resolve/main/eval_results.json
239 Bytes
| { | |
| "epoch": 5.0, | |
| "eval_loss": 0.727217972278595, | |
| "eval_matthews_correlation": 0.565965534490769, | |
| "eval_runtime": 2.1066, | |
| "eval_samples": 1043, | |
| "eval_samples_per_second": 495.099, | |
| "eval_steps_per_second": 62.184 | |
| } |