Text Classification
Transformers
PyTorch
English
promptforge_quality
promptforge
prompt-engineering
prompt-quality
modernbert
regression
llm
Instructions to use ArjunShukla/PromptForge-Quality with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArjunShukla/PromptForge-Quality with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ArjunShukla/PromptForge-Quality")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ArjunShukla/PromptForge-Quality", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 422 Bytes
333fb24 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | {
"model_type": "promptforge_quality",
"base_model_name": "answerdotai/ModernBERT-base",
"num_labels": 7,
"dropout": 0.1,
"dimension_loss_weight": 0.8,
"quality_loss_weight": 0.2,
"label_names": [
"clarity",
"specificity",
"context",
"goal_definition",
"constraints",
"completeness",
"actionability"
],
"architectures": [
"PromptForgeQualityModel"
]
} |