Text Classification
Transformers
TensorFlow
roberta
generated_from_keras_callback
text-embeddings-inference
Instructions to use braindao/iq-code-supervisor-missing-return-statement-v1-tinyroberta-6l-768d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use braindao/iq-code-supervisor-missing-return-statement-v1-tinyroberta-6l-768d with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="braindao/iq-code-supervisor-missing-return-statement-v1-tinyroberta-6l-768d")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("braindao/iq-code-supervisor-missing-return-statement-v1-tinyroberta-6l-768d") model = AutoModelForSequenceClassification.from_pretrained("braindao/iq-code-supervisor-missing-return-statement-v1-tinyroberta-6l-768d", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epochs": 2, | |
| "learning_rate": 1e-05, | |
| "model_name": "deepset/tinyroberta-6l-768d", | |
| "evaluation": [ | |
| 0.0008178171037303006, | |
| 0.0007848538627519552, | |
| 0.9992092289536872, | |
| 0.0007827766833699012, | |
| 0.9991875151053535, | |
| 0.0007897196128086037, | |
| 0.999194377478458, | |
| 0.0007847069126737383, | |
| 0.9991912057171757, | |
| 0.0007855461690940979, | |
| 0.9991958935677381, | |
| 0.000785352314220833, | |
| 0.9991970388540179, | |
| 0.0007879251506279772, | |
| 0.9991914060750224, | |
| 0.0007884886635244337, | |
| 0.9992020577928902, | |
| 0.0007888689475750166, | |
| 0.9992294733418028, | |
| 0.0007840781050665324, | |
| 0.9992103814093027, | |
| 0.0007828270352403521, | |
| 0.9992048671582784, | |
| 0.0007829428568245644, | |
| 0.9992107893169417 | |
| ] | |
| } |