Text Classification
Transformers
Safetensors
English
bert
software-engineering
automated-program-repair
retrieval
routing
cross-encoder
swe-bench
context-sphere
text-embeddings-inference
Instructions to use Zywdd/context-sphere-projector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Zywdd/context-sphere-projector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Zywdd/context-sphere-projector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Zywdd/context-sphere-projector") model = AutoModelForSequenceClassification.from_pretrained("Zywdd/context-sphere-projector") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 1, | |
| "global_step": 467, | |
| "train_loss": 1.7938466038419296, | |
| "validation_loss": 1.3247293804639153, | |
| "worker_f1_at_0_5": 0.1694915254237288, | |
| "worker_margin": 0.18419288120725416, | |
| "worker_negative_mean": 0.18152672360015024, | |
| "worker_positive_mean": 0.3657196048074044, | |
| "worker_recall_at_0_5": 0.38461538461538464 | |
| } | |