Text Classification
Transformers
Safetensors
German
llama
feature-extraction
reranker
cross-encoder
german
retrieval
rag
on-prem
text-embeddings-inference
Instructions to use keyvan-ai/Mankei-326M-Reranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use keyvan-ai/Mankei-326M-Reranker with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="keyvan-ai/Mankei-326M-Reranker")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("keyvan-ai/Mankei-326M-Reranker") model = AutoModel.from_pretrained("keyvan-ai/Mankei-326M-Reranker", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Benchmark-Grafik eingebettet
Browse files
README.md
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Der spezialisierte deutsche Reranker liegt vor dem multilingualen SOTA-Reranker (bge-reranker-v2-m3) und dem deutschen mMARCO-Cross-Encoder.
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## Verwendung
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```python
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from transformers import AutoModel, AutoTokenizer
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Der spezialisierte deutsche Reranker liegt vor dem multilingualen SOTA-Reranker (bge-reranker-v2-m3) und dem deutschen mMARCO-Cross-Encoder.
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## Verwendung
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```python
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from transformers import AutoModel, AutoTokenizer
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