Instructions to use dusersad12/FineTunedBest-TestRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dusersad12/FineTunedBest-TestRepo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dusersad12/FineTunedBest-TestRepo")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dusersad12/FineTunedBest-TestRepo") model = AutoModelForSequenceClassification.from_pretrained("dusersad12/FineTunedBest-TestRepo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload FineTunedBest model (run_gamma, best by eval_accuracy) with filled-in benchmark scores
8ef5ecf verified Download config.json from dusersad12/FineTunedBest-TestRepo: direct link, hf CLI and curl.
- Browser
- Download file 170 Bytes
-
https://huggingface.co/dusersad12/FineTunedBest-TestRepo/resolve/main/config.json
- Command line
-
hf download hf://dusersad12/FineTunedBest-TestRepo/config.json
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curl -L -o config.json https://huggingface.co/dusersad12/FineTunedBest-TestRepo/resolve/main/config.json
170 Bytes
| { | |
| "model_type": "roberta", | |
| "architectures": ["RobertaForSequenceClassification"], | |
| "learning_rate": 5e-05, | |
| "num_train_epochs": 5, | |
| "batch_size": 8, | |
| "seed": 21 | |
| } |