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: 374 Bytes
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"backend": "tokenizers",
"cls_token": "[CLS]",
"do_basic_tokenize": true,
"do_lower_case": true,
"is_local": false,
"mask_token": "[MASK]",
"model_max_length": 512,
"never_split": null,
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"strip_accents": null,
"tokenize_chinese_chars": true,
"tokenizer_class": "BertTokenizer",
"unk_token": "[UNK]"
}
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