Text Classification
Transformers
ONNX
PEFT
English
cross-encoder
reranker
thread-matching
conversational-ai
lora
Eval Results (legacy)
Instructions to use Algokruti/thread-reranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Algokruti/thread-reranker with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Algokruti/thread-reranker")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Algokruti/thread-reranker", dtype="auto") - PEFT
How to use Algokruti/thread-reranker with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
File size: 330 Bytes
6faa13d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"base_model": "microsoft/MiniLM-L6-H384-uncased",
"lora_r": 8,
"lora_alpha": 16,
"num_structured_features": 5,
"structured_feature_names": [
"entity_overlap",
"keyword_matches",
"flow_continuity",
"recency_score",
"hours_since_active"
],
"max_length": 256,
"best_val_f1": 0.5887755102040816
} |