Instructions to use israel/testing_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use israel/testing_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="israel/testing_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("israel/testing_model") model = AutoModelForSequenceClassification.from_pretrained("israel/testing_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download all_results.json from israel/testing_model: direct link, hf CLI and curl.
- Browser
- Download file 337 Bytes
-
https://huggingface.co/israel/testing_model/resolve/main/all_results.json
- Command line
-
hf download hf://israel/testing_model/all_results.json
-
curl -L -o all_results.json https://huggingface.co/israel/testing_model/resolve/main/all_results.json
337 Bytes
| { | |
| "epoch": 5.0, | |
| "predict_runtime": 3.2345, | |
| "predict_samples": 1497, | |
| "predict_samples_per_second": 462.819, | |
| "predict_steps_per_second": 58.123, | |
| "train_loss": 1.0310750216723763, | |
| "train_runtime": 163.2592, | |
| "train_samples": 5984, | |
| "train_samples_per_second": 183.267, | |
| "train_steps_per_second": 5.727 | |
| } |